Head of AI / Director of AI (Hands-On) Manchester (On-site) Shape the AI strategy and build it yourself. An award-winning international professional services organisation, with a strong record of year-on-year growth, is investing significantly in AI and is looking for a Head of AI / Director of AI to lead the way. This is a fully on-site role based at their Manchester office. Our client is a market leader in B2B consultancy, providing critical legal and professional support services that help businesses manage complexity, stay compliant and grow. This role is for someone who wants to set the direction and stay close to the AI engineering. You'll define the AI vision and roadmap, and you'll also roll up your sleeves to design, build and deploy solutions that make a real difference to clients and the business. You'll move AI beyond experimentation and into production, and shape how professional expertise is delivered at scale. Open to established leaders and those ready to step up. We'd love to hear from current Directors or Heads of AI, as well as Lead or Principal AI/ML Engineers who are ready for their first senior leadership role. What you'll do Define and lead the organisation's AI strategy and roadmap, reporting into the senior leadership team. Stay hands-on: architect, build and deploy AI solutions into production, and set the technical standard for the team. Identify and deliver AI opportunities across client services, professional delivery, internal operations, knowledge management and commercial growth. Work with Generative AI, LLMs, Machine Learning, RAG, vector search and knowledge graphs. Build and lead a cross-functional AI team, bringing together engineers and professional subject matter experts. Establish practical AI governance, covering security, privacy, compliance, accuracy, explainability and responsible AI. Partner with senior leaders to turn AI opportunities into measurable client and commercial outcomes. About you Strong hands-on experience taking Machine Learning and Generative AI solutions into production, including RAG architectures. Deep technical knowledge of LLMs, NLP, Python, SQL and frameworks such as PyTorch or TensorFlow. A solid understanding of MLOps, DevOps, CI/CD and DevSecOps. Experience leading AI initiatives or technical teams, whether as a Director, Head of AI, or Lead or Principal Engineer. The ability to talk strategy in the boardroom and architecture with engineers, with the commercial judgement to know what will make an impact. Experience in professional services, consulting, legal, HR, compliance or another knowledge-intensive environment is a bonus, but not essential. Why this role? A rare chance to shape AI at a pivotal point in a high-growth, multi-award-winning organisation. Real autonomy to build the strategy, the team and the technology. Close working with an ambitious leadership team, influencing the company's next phase of growth. A competitive salary, performance bonus, private healthcare, pension and premium benefits. INDAM The Portfolio Group are acting on behalf of our client in recruiting for this position.
Oct 23, 2026
Full time
Head of AI / Director of AI (Hands-On) Manchester (On-site) Shape the AI strategy and build it yourself. An award-winning international professional services organisation, with a strong record of year-on-year growth, is investing significantly in AI and is looking for a Head of AI / Director of AI to lead the way. This is a fully on-site role based at their Manchester office. Our client is a market leader in B2B consultancy, providing critical legal and professional support services that help businesses manage complexity, stay compliant and grow. This role is for someone who wants to set the direction and stay close to the AI engineering. You'll define the AI vision and roadmap, and you'll also roll up your sleeves to design, build and deploy solutions that make a real difference to clients and the business. You'll move AI beyond experimentation and into production, and shape how professional expertise is delivered at scale. Open to established leaders and those ready to step up. We'd love to hear from current Directors or Heads of AI, as well as Lead or Principal AI/ML Engineers who are ready for their first senior leadership role. What you'll do Define and lead the organisation's AI strategy and roadmap, reporting into the senior leadership team. Stay hands-on: architect, build and deploy AI solutions into production, and set the technical standard for the team. Identify and deliver AI opportunities across client services, professional delivery, internal operations, knowledge management and commercial growth. Work with Generative AI, LLMs, Machine Learning, RAG, vector search and knowledge graphs. Build and lead a cross-functional AI team, bringing together engineers and professional subject matter experts. Establish practical AI governance, covering security, privacy, compliance, accuracy, explainability and responsible AI. Partner with senior leaders to turn AI opportunities into measurable client and commercial outcomes. About you Strong hands-on experience taking Machine Learning and Generative AI solutions into production, including RAG architectures. Deep technical knowledge of LLMs, NLP, Python, SQL and frameworks such as PyTorch or TensorFlow. A solid understanding of MLOps, DevOps, CI/CD and DevSecOps. Experience leading AI initiatives or technical teams, whether as a Director, Head of AI, or Lead or Principal Engineer. The ability to talk strategy in the boardroom and architecture with engineers, with the commercial judgement to know what will make an impact. Experience in professional services, consulting, legal, HR, compliance or another knowledge-intensive environment is a bonus, but not essential. Why this role? A rare chance to shape AI at a pivotal point in a high-growth, multi-award-winning organisation. Real autonomy to build the strategy, the team and the technology. Close working with an ambitious leadership team, influencing the company's next phase of growth. A competitive salary, performance bonus, private healthcare, pension and premium benefits. INDAM The Portfolio Group are acting on behalf of our client in recruiting for this position.
MACHINE LEARNING ENGINEERING LEAD UP TO £125,000 LONDON This is an excellent opportunity for an experienced ML Engineering Manager or technical leader to join a high-growth fintech and take ownership of a growing machine learning engineering function. You'll combine hands-on technical contribution with people leadership, helping scale production ML systems while shaping the future direction of the team. THE COMPANY Our client is a growing fintech with a strong engineering culture and investment in data. Machine learning forms a critical part of their technology strategy, creating an environment where engineering teams have a direct impact on business outcomes. As the company continues to scale, they are investing in maturing their ML platform and expanding their engineering capabilities. THE ROLE Responsibilities include but are not limited to: Lead and develop a team of ML and MLOps engineers Own delivery, operational performance, and technical execution across the ML Engineering function Drive the evolution of machine learning infrastructure, deployment pipelines, and MLOps capabilities Contribute hands-on to architecture, platform development, and production ML initiatives Help shape the long-term strategy, growth, and maturity of the ML Engineering function YOUR SKILLS AND EXPERIENCE : Previous people management or engineering leadership experience Strong commercial experience in Software Engineering, ML Engineering, or MLOps environments Experience building, deploying, and supporting machine learning solutions at scale Experience working with AWS and ML tooling such as MLflow, Airflow, Metaflow, or Snowflake Ability to balance technical leadership, strategic thinking, and hands-on engineering contribution SALARY AND BENEFITS Up to £125,000 base salary Contributory pension scheme HOW TO APPLY Please register your interest to Mia Randhawa by sending your CV through the 'Apply' link
Oct 23, 2026
Full time
MACHINE LEARNING ENGINEERING LEAD UP TO £125,000 LONDON This is an excellent opportunity for an experienced ML Engineering Manager or technical leader to join a high-growth fintech and take ownership of a growing machine learning engineering function. You'll combine hands-on technical contribution with people leadership, helping scale production ML systems while shaping the future direction of the team. THE COMPANY Our client is a growing fintech with a strong engineering culture and investment in data. Machine learning forms a critical part of their technology strategy, creating an environment where engineering teams have a direct impact on business outcomes. As the company continues to scale, they are investing in maturing their ML platform and expanding their engineering capabilities. THE ROLE Responsibilities include but are not limited to: Lead and develop a team of ML and MLOps engineers Own delivery, operational performance, and technical execution across the ML Engineering function Drive the evolution of machine learning infrastructure, deployment pipelines, and MLOps capabilities Contribute hands-on to architecture, platform development, and production ML initiatives Help shape the long-term strategy, growth, and maturity of the ML Engineering function YOUR SKILLS AND EXPERIENCE : Previous people management or engineering leadership experience Strong commercial experience in Software Engineering, ML Engineering, or MLOps environments Experience building, deploying, and supporting machine learning solutions at scale Experience working with AWS and ML tooling such as MLflow, Airflow, Metaflow, or Snowflake Ability to balance technical leadership, strategic thinking, and hands-on engineering contribution SALARY AND BENEFITS Up to £125,000 base salary Contributory pension scheme HOW TO APPLY Please register your interest to Mia Randhawa by sending your CV through the 'Apply' link
Job Title: Engineering Manager, AI Company: 167 Solutions Location: Hybrid (UK ONLY) Salary: £150,000 - £170,000 per annum Contract Type: Permanent Experience Level: Minimum 5 years' experience Start Date: ASAP The Opportunity: 167Solutions is partnering with a globally recognised media and information services organisation to recruit an Engineering Manager - Applied AI & Data Science . Our client is at the forefront of digital innovation, investing heavily in artificial intelligence, machine learning and data science to transform how millions of people access and interact with trusted information. The role combines people leadership, technical architecture and hands-on engineering, with a particular focus on generative AI, agentic systems, LLMOps and AI-native software development. You'll play a key role in shaping the organisation's AI capabilities, delivering production-grade AI systems and driving the adoption of modern AI engineering practices. The Role: As Engineering Manager, you will lead the Applied AI and Data Science team, taking ownership of technical delivery, team development and engineering standards while remaining actively involved in designing and building AI solutions. You will work closely with senior AI leadership, product managers, data engineers and business stakeholders to translate ambitious AI initiatives into scalable, secure and commercially valuable solutions. The team's work spans large language models, agentic AI, retrieval-augmented generation (RAG), natural language processing, predictive modelling and shared AI platform capabilities. What You'll Do: Lead and develop a multidisciplinary AI team , providing day-to-day management, mentorship, technical guidance and career development for AI/ML Engineers, NLP Engineers and Data Scientists. Own technical delivery , managing priorities, resources and engineering commitments while balancing rapid experimentation with production requirements. Remain hands-on , contributing Python code, reviewing models and implementations, prototyping solutions and supporting complex technical challenges. Shape AI architecture , guiding the design and development of agentic AI systems, RAG pipelines, NLP solutions and machine learning applications. Build safe and reliable AI agents , implementing appropriate guardrails, tool permissions, human-in-the-loop controls and end-to-end evaluation. Drive AI-native software engineering , introducing and scaling the use of tools such as Claude Code, Cursor and GitHub Copilot across development, testing and code review. Establish engineering best practices , covering LLMOps, MLOps, CI/CD, automated evaluation, observability, security, performance and cost optimisation. Work extensively with AWS AI services , including Amazon Bedrock, Bedrock AgentCore, SageMaker, Lambda and Step Functions. What We Are Looking For: Proven experience as an Engineering Manager or Technical Lead with direct people-management responsibility for AI Engineers, ML Engineers, NLP Engineers or Data Scientists. Strong hands-on AI/ML engineering background, with advanced Python skills and experience developing production-grade AI systems. Experience designing and building LLM-powered and agentic AI applications, including RAG, NLP and traditional machine learning solutions. Practical experience with modern agent frameworks such as LangGraph, Strands Agents or Claude Agent SDK, alongside interoperability standards including MCP and A2A. Strong AWS cloud engineering experience, particularly Amazon Bedrock, Bedrock AgentCore, SageMaker, Lambda and Step Functions, with Infrastructure as Code using AWS CDK or equivalent. Hands-on experience with LLMOps and MLOps, including model and agent evaluation, trajectory testing, tracing, observability, guardrails and cost monitoring. Understanding of AI security challenges, including prompt injection, data leakage, excessive agent permissions and appropriate mitigation strategies. Experience using AI coding assistants and agents, such as Claude Code, Cursor or GitHub Copilot, throughout the software development lifecycle. Ability to establish engineering standards for AI-generated code, context engineering, automated testing and AI-assisted development. Desirable Experience: Experience building and operating production-grade agentic AI systems, including multi-agent orchestration, agent memory, MCP-based tool integration and agentic RAG. Strong NLP expertise, including semantic search, summarisation, information extraction, classification or LLM fine-tuning. Experience developing shared AI platforms, internal MCP servers or reusable AI capabilities used by multiple engineering teams. Knowledge of vector search technologies such as OpenSearch, Amazon S3 Vectors or pgvector. Familiarity with AI governance, regulatory considerations and responsible AI development practices. Why Join Us: This is an opportunity to take a leading role in a major AI transformation programme within a globally established, highly respected organisation. You'll be working on meaningful AI initiatives with the potential to impact millions of users, while helping shape the technical direction and engineering culture of a growing Applied AI and Data Science function. The position offers a rare combination of hands-on technical ownership, people leadership and strategic influence, giving you the opportunity to work with cutting-edge agentic AI technologies while building and developing a high-performing engineering team. If you're an experienced AI Engineering Manager who wants to remain close to the technology, lead talented engineers and data scientists, and help deliver the next generation of AI-powered products, we'd love to hear from you.
Oct 23, 2026
Full time
Job Title: Engineering Manager, AI Company: 167 Solutions Location: Hybrid (UK ONLY) Salary: £150,000 - £170,000 per annum Contract Type: Permanent Experience Level: Minimum 5 years' experience Start Date: ASAP The Opportunity: 167Solutions is partnering with a globally recognised media and information services organisation to recruit an Engineering Manager - Applied AI & Data Science . Our client is at the forefront of digital innovation, investing heavily in artificial intelligence, machine learning and data science to transform how millions of people access and interact with trusted information. The role combines people leadership, technical architecture and hands-on engineering, with a particular focus on generative AI, agentic systems, LLMOps and AI-native software development. You'll play a key role in shaping the organisation's AI capabilities, delivering production-grade AI systems and driving the adoption of modern AI engineering practices. The Role: As Engineering Manager, you will lead the Applied AI and Data Science team, taking ownership of technical delivery, team development and engineering standards while remaining actively involved in designing and building AI solutions. You will work closely with senior AI leadership, product managers, data engineers and business stakeholders to translate ambitious AI initiatives into scalable, secure and commercially valuable solutions. The team's work spans large language models, agentic AI, retrieval-augmented generation (RAG), natural language processing, predictive modelling and shared AI platform capabilities. What You'll Do: Lead and develop a multidisciplinary AI team , providing day-to-day management, mentorship, technical guidance and career development for AI/ML Engineers, NLP Engineers and Data Scientists. Own technical delivery , managing priorities, resources and engineering commitments while balancing rapid experimentation with production requirements. Remain hands-on , contributing Python code, reviewing models and implementations, prototyping solutions and supporting complex technical challenges. Shape AI architecture , guiding the design and development of agentic AI systems, RAG pipelines, NLP solutions and machine learning applications. Build safe and reliable AI agents , implementing appropriate guardrails, tool permissions, human-in-the-loop controls and end-to-end evaluation. Drive AI-native software engineering , introducing and scaling the use of tools such as Claude Code, Cursor and GitHub Copilot across development, testing and code review. Establish engineering best practices , covering LLMOps, MLOps, CI/CD, automated evaluation, observability, security, performance and cost optimisation. Work extensively with AWS AI services , including Amazon Bedrock, Bedrock AgentCore, SageMaker, Lambda and Step Functions. What We Are Looking For: Proven experience as an Engineering Manager or Technical Lead with direct people-management responsibility for AI Engineers, ML Engineers, NLP Engineers or Data Scientists. Strong hands-on AI/ML engineering background, with advanced Python skills and experience developing production-grade AI systems. Experience designing and building LLM-powered and agentic AI applications, including RAG, NLP and traditional machine learning solutions. Practical experience with modern agent frameworks such as LangGraph, Strands Agents or Claude Agent SDK, alongside interoperability standards including MCP and A2A. Strong AWS cloud engineering experience, particularly Amazon Bedrock, Bedrock AgentCore, SageMaker, Lambda and Step Functions, with Infrastructure as Code using AWS CDK or equivalent. Hands-on experience with LLMOps and MLOps, including model and agent evaluation, trajectory testing, tracing, observability, guardrails and cost monitoring. Understanding of AI security challenges, including prompt injection, data leakage, excessive agent permissions and appropriate mitigation strategies. Experience using AI coding assistants and agents, such as Claude Code, Cursor or GitHub Copilot, throughout the software development lifecycle. Ability to establish engineering standards for AI-generated code, context engineering, automated testing and AI-assisted development. Desirable Experience: Experience building and operating production-grade agentic AI systems, including multi-agent orchestration, agent memory, MCP-based tool integration and agentic RAG. Strong NLP expertise, including semantic search, summarisation, information extraction, classification or LLM fine-tuning. Experience developing shared AI platforms, internal MCP servers or reusable AI capabilities used by multiple engineering teams. Knowledge of vector search technologies such as OpenSearch, Amazon S3 Vectors or pgvector. Familiarity with AI governance, regulatory considerations and responsible AI development practices. Why Join Us: This is an opportunity to take a leading role in a major AI transformation programme within a globally established, highly respected organisation. You'll be working on meaningful AI initiatives with the potential to impact millions of users, while helping shape the technical direction and engineering culture of a growing Applied AI and Data Science function. The position offers a rare combination of hands-on technical ownership, people leadership and strategic influence, giving you the opportunity to work with cutting-edge agentic AI technologies while building and developing a high-performing engineering team. If you're an experienced AI Engineering Manager who wants to remain close to the technology, lead talented engineers and data scientists, and help deliver the next generation of AI-powered products, we'd love to hear from you.
FULL STACK SOFTWARE ENGINEER - AI/ML - SECURITY CLEARED NEW PERMANENT OPPORTUNITY AVAILABLE FOR A SC OR MOD DV CLEARED FULL STACK SOFTWARE ENGINEER WITH AN INTEREST IN AI/ML Salary: Up to £90,000 Location: West London Clearance: Active SC or MOD DV Clearance required Employment: Permanent Sector: National Security & Defence To apply, email: Searchability NS&D are working with a growing technology organisation delivering advanced software and AI capabilities across the National Security & Defence sector. They are looking for an all-round Full Stack Software Engineer with an interest in AI/ML to join a highly technical engineering team. This isn't a role where you'll be expected to be a dedicated Machine Learning Engineer or pure frontend developer. We're looking for someone comfortable getting involved across the software stack, solving difficult engineering problems and working alongside AI/ML specialists to turn emerging technology into usable, production-ready software. THE ROLE You'll work across the software development lifecycle, helping to design, build, integrate and deploy applications that make advanced AI and computer vision capabilities accessible to end users. The role could involve: Developing modern full stack applications and user interfaces Building backend services and REST APIs Integrating AI/ML capabilities into software applications Developing tools for image, video and AI visualisation Building scalable and maintainable software Integrating applications, services and workflows Working with data and modern data platforms Contributing to software architecture and technical direction Developing automated tests and CI/CD pipelines Supporting customer demonstrations, trials and deployments Working with AI/ML teams to turn research and models into practical software The balance of frontend, backend, integration and AI/ML work will depend on your experience and interests. WHAT WE'RE LOOKING FOR We're deliberately looking for an all-rounder rather than someone who ticks every box. You'll ideally have several years of commercial Software Engineering experience and be comfortable working across different parts of the technology stack. Experience with some of the following would be valuable: SOFTWARE ENGINEERING Full Stack Software Development Python development JavaScript / TypeScript or similar frontend technologies REST APIs and frameworks such as Flask or Django Git, automated testing and CI/CD Strong software design and engineering practices Linux development environments DATA & INTEGRATION Application or systems integration Databases such as MongoDB or PostgreSQL Data lakes / modern data platforms Event-driven architectures or messaging Building connected workflows between different systems AI / ML Experience working alongside AI/ML or data science teams Exposure to Machine Learning or Computer Vision Python-based ML technologies such as PyTorch ML pipelines or model deployment Image or video processing An interest in integrating AI/ML into production software You don't need experience across all of these areas - a strong software engineer with breadth, curiosity and an interest in AI/ML is exactly what we're looking for. WHY JOIN? You'll be joining a highly technical team working on genuinely challenging software and AI problems, with the opportunity to see your work move from development into real-world operational environments. You'll have the opportunity to: Work alongside experienced Software Engineers, AI/ML specialists and researchers Build software around cutting-edge AI and Computer Vision technology Work across software engineering, integration and AI/ML Influence architecture and technical direction Take ownership of meaningful projects Develop your skills across modern technologies Contribute to products designed for demanding real-world environments SECURITY CLEARANCE Due to the nature of the work, active SC or MOD DV clearance is required for this position. APPLY NOW If you're an SC or MOD DV cleared Software Engineer who enjoys working across the stack and has an interest in AI/ML, Computer Vision or emerging technologies, we'd love to hear from you. You don't need to be an AI expert - we're particularly interested in engineers with a broad technical skillset who want to get closer to this area.
Oct 23, 2026
Full time
FULL STACK SOFTWARE ENGINEER - AI/ML - SECURITY CLEARED NEW PERMANENT OPPORTUNITY AVAILABLE FOR A SC OR MOD DV CLEARED FULL STACK SOFTWARE ENGINEER WITH AN INTEREST IN AI/ML Salary: Up to £90,000 Location: West London Clearance: Active SC or MOD DV Clearance required Employment: Permanent Sector: National Security & Defence To apply, email: Searchability NS&D are working with a growing technology organisation delivering advanced software and AI capabilities across the National Security & Defence sector. They are looking for an all-round Full Stack Software Engineer with an interest in AI/ML to join a highly technical engineering team. This isn't a role where you'll be expected to be a dedicated Machine Learning Engineer or pure frontend developer. We're looking for someone comfortable getting involved across the software stack, solving difficult engineering problems and working alongside AI/ML specialists to turn emerging technology into usable, production-ready software. THE ROLE You'll work across the software development lifecycle, helping to design, build, integrate and deploy applications that make advanced AI and computer vision capabilities accessible to end users. The role could involve: Developing modern full stack applications and user interfaces Building backend services and REST APIs Integrating AI/ML capabilities into software applications Developing tools for image, video and AI visualisation Building scalable and maintainable software Integrating applications, services and workflows Working with data and modern data platforms Contributing to software architecture and technical direction Developing automated tests and CI/CD pipelines Supporting customer demonstrations, trials and deployments Working with AI/ML teams to turn research and models into practical software The balance of frontend, backend, integration and AI/ML work will depend on your experience and interests. WHAT WE'RE LOOKING FOR We're deliberately looking for an all-rounder rather than someone who ticks every box. You'll ideally have several years of commercial Software Engineering experience and be comfortable working across different parts of the technology stack. Experience with some of the following would be valuable: SOFTWARE ENGINEERING Full Stack Software Development Python development JavaScript / TypeScript or similar frontend technologies REST APIs and frameworks such as Flask or Django Git, automated testing and CI/CD Strong software design and engineering practices Linux development environments DATA & INTEGRATION Application or systems integration Databases such as MongoDB or PostgreSQL Data lakes / modern data platforms Event-driven architectures or messaging Building connected workflows between different systems AI / ML Experience working alongside AI/ML or data science teams Exposure to Machine Learning or Computer Vision Python-based ML technologies such as PyTorch ML pipelines or model deployment Image or video processing An interest in integrating AI/ML into production software You don't need experience across all of these areas - a strong software engineer with breadth, curiosity and an interest in AI/ML is exactly what we're looking for. WHY JOIN? You'll be joining a highly technical team working on genuinely challenging software and AI problems, with the opportunity to see your work move from development into real-world operational environments. You'll have the opportunity to: Work alongside experienced Software Engineers, AI/ML specialists and researchers Build software around cutting-edge AI and Computer Vision technology Work across software engineering, integration and AI/ML Influence architecture and technical direction Take ownership of meaningful projects Develop your skills across modern technologies Contribute to products designed for demanding real-world environments SECURITY CLEARANCE Due to the nature of the work, active SC or MOD DV clearance is required for this position. APPLY NOW If you're an SC or MOD DV cleared Software Engineer who enjoys working across the stack and has an interest in AI/ML, Computer Vision or emerging technologies, we'd love to hear from you. You don't need to be an AI expert - we're particularly interested in engineers with a broad technical skillset who want to get closer to this area.
SENIOR PYTHON SOFTWARE ENGINEER - SC / DV CLEARED NEW PERMANENT OPPORTUNITY AVAILABLE Salary: Up to £100,000 base Location: London Working Pattern: Hybrid - 2-4 days per week on-site Clearance: Active SC or DV Type: Permanent I'm currently working with an organisation delivering innovative AI and software solutions within the UK Defence sector, who are looking for a strong Python Backend Engineer with knowledge of machine learning to join their growing team. THE ROLE This is a hands-on engineering role focused on building scalable backend applications, services and infrastructure that support AI and machine learning solutions. You'll work alongside data scientists and other engineers to turn ML capabilities into reliable, production-ready software, with a focus on software engineering rather than developing models from scratch. Responsibilities include: Designing, developing and maintaining scalable backend applications and services using Python. Building APIs, integrations and software infrastructure to support AI and machine learning solutions. Working alongside data scientists to integrate and operationalise ML models within production systems. Developing reusable software components and tools to improve the delivery of AI-enabled applications. Working with cloud platforms such as AWS, Azure or GCP. Using Docker and Kubernetes to build, deploy and manage applications at scale. Contributing to software architecture, technical design and engineering best practices. Making technical decisions to ensure solutions are scalable, secure and maintainable. Collaborating with engineers, data scientists and client stakeholders to deliver complex technical projects. WHAT THEY'RE LOOKING FOR Strong commercial experience developing backend applications and services using Python. Solid software engineering fundamentals, including clean code, testing and maintainable system design. Experience building APIs, integrations and scalable software systems. Knowledge of machine learning concepts and an understanding of how ML models are deployed and used in production. Experience working with ML-enabled applications or integrating models built using frameworks such as Scikit-learn, TensorFlow or PyTorch. Experience with cloud platforms such as AWS, Azure or GCP. Familiarity with Docker, Kubernetes and modern software deployment practices. An understanding of infrastructure, application security and production environments. Strong problem-solving skills and the ability to collaborate with multidisciplinary teams. Active SC or DV security clearance. INTERESTED? If you're an SC or DV-cleared Python Backend Engineer with strong software engineering skills and knowledge of machine learning, get in touch to discuss the opportunity. To apply, please send over your latest CV.
Oct 23, 2026
Full time
SENIOR PYTHON SOFTWARE ENGINEER - SC / DV CLEARED NEW PERMANENT OPPORTUNITY AVAILABLE Salary: Up to £100,000 base Location: London Working Pattern: Hybrid - 2-4 days per week on-site Clearance: Active SC or DV Type: Permanent I'm currently working with an organisation delivering innovative AI and software solutions within the UK Defence sector, who are looking for a strong Python Backend Engineer with knowledge of machine learning to join their growing team. THE ROLE This is a hands-on engineering role focused on building scalable backend applications, services and infrastructure that support AI and machine learning solutions. You'll work alongside data scientists and other engineers to turn ML capabilities into reliable, production-ready software, with a focus on software engineering rather than developing models from scratch. Responsibilities include: Designing, developing and maintaining scalable backend applications and services using Python. Building APIs, integrations and software infrastructure to support AI and machine learning solutions. Working alongside data scientists to integrate and operationalise ML models within production systems. Developing reusable software components and tools to improve the delivery of AI-enabled applications. Working with cloud platforms such as AWS, Azure or GCP. Using Docker and Kubernetes to build, deploy and manage applications at scale. Contributing to software architecture, technical design and engineering best practices. Making technical decisions to ensure solutions are scalable, secure and maintainable. Collaborating with engineers, data scientists and client stakeholders to deliver complex technical projects. WHAT THEY'RE LOOKING FOR Strong commercial experience developing backend applications and services using Python. Solid software engineering fundamentals, including clean code, testing and maintainable system design. Experience building APIs, integrations and scalable software systems. Knowledge of machine learning concepts and an understanding of how ML models are deployed and used in production. Experience working with ML-enabled applications or integrating models built using frameworks such as Scikit-learn, TensorFlow or PyTorch. Experience with cloud platforms such as AWS, Azure or GCP. Familiarity with Docker, Kubernetes and modern software deployment practices. An understanding of infrastructure, application security and production environments. Strong problem-solving skills and the ability to collaborate with multidisciplinary teams. Active SC or DV security clearance. INTERESTED? If you're an SC or DV-cleared Python Backend Engineer with strong software engineering skills and knowledge of machine learning, get in touch to discuss the opportunity. To apply, please send over your latest CV.
AI Software Engineer - UKSV DV Cleared NEW PERMANENT OPPORTUNITY AVAILABLE FOR AN AI SOFTWARE ENGINEER WITH DV CLEARANCE Salary : Up to £130,000 Location : London Working Pattern: Hybrid Clearance : Active UKSV DV To Apply, email : I'm currently working with a leading AI organisation operating within the National Security space, who are looking for an experienced AI Software Engineer to join their team. This is an opportunity to work on technically challenging projects, focusing on building, deploying and scaling machine learning systems in production environments. The role is heavily focused on Python software engineering, ML deployment and cloud infrastructure, working alongside engineers, data scientists and technical stakeholders to deliver robust, production-grade solutions for complex client challenges. THE ROLE You'll play a key role in taking machine learning models from development into production, building the software, tools and infrastructure required to deploy and operate ML systems reliably at scale. Working across software engineering, cloud architecture and machine learning operations, you'll help develop reusable solutions, influence technical decisions and establish best practices for deploying machine learning in production environments. You'll also work directly with clients and cross-functional teams, helping shape technical solutions, assess feasibility and ensure successful delivery. WHAT YOU'LL BE DOING Building and deploying production-grade machine learning software, tools and infrastructure. Developing reusable, scalable solutions to accelerate the delivery of ML systems. Operationalising machine learning models built using frameworks such as Scikit-learn, TensorFlow or PyTorch. Working across cloud platforms and infrastructure, including architecture and security considerations. Using Docker and Kubernetes to build, deploy and manage applications at scale. Contributing to technical scoping, software architecture and engineering best practices. Collaborating with software engineers, data scientists and commercial teams to solve complex client challenges. Advising customers and partners on technical approaches, translating complex concepts for non-technical stakeholders. Helping define standards and best practices for deploying machine learning systems at scale. WHAT I'M LOOKING FOR Strong Python development skills and a solid understanding of software engineering best practices. Experience taking machine learning models from development through to production. Understanding of the full machine learning lifecycle and experience operationalising models built with frameworks such as Scikit-learn, TensorFlow or PyTorch. Hands-on experience with cloud platforms such as AWS, Azure or GCP, including infrastructure, architecture and security. Experience with Docker and Kubernetes. A sound understanding of core machine learning concepts, including probability, statistics and common learning techniques. Strong communication skills, with the ability to advise technical teams and engage confidently with non-technical stakeholders. The ability to take ownership of technical scope, make informed decisions and deliver solutions in a fast-paced environment. Active UKSV DV clearance. THE OPPORTUNITY You'll join a team working at the intersection of software engineering and machine learning, helping bring ML systems into real-world use across critical client environments. This is a strong opportunity for a software engineer with hands-on ML deployment experience who enjoys solving complex technical problems, building scalable infrastructure and taking ownership of production-grade solutions.
Oct 23, 2026
Full time
AI Software Engineer - UKSV DV Cleared NEW PERMANENT OPPORTUNITY AVAILABLE FOR AN AI SOFTWARE ENGINEER WITH DV CLEARANCE Salary : Up to £130,000 Location : London Working Pattern: Hybrid Clearance : Active UKSV DV To Apply, email : I'm currently working with a leading AI organisation operating within the National Security space, who are looking for an experienced AI Software Engineer to join their team. This is an opportunity to work on technically challenging projects, focusing on building, deploying and scaling machine learning systems in production environments. The role is heavily focused on Python software engineering, ML deployment and cloud infrastructure, working alongside engineers, data scientists and technical stakeholders to deliver robust, production-grade solutions for complex client challenges. THE ROLE You'll play a key role in taking machine learning models from development into production, building the software, tools and infrastructure required to deploy and operate ML systems reliably at scale. Working across software engineering, cloud architecture and machine learning operations, you'll help develop reusable solutions, influence technical decisions and establish best practices for deploying machine learning in production environments. You'll also work directly with clients and cross-functional teams, helping shape technical solutions, assess feasibility and ensure successful delivery. WHAT YOU'LL BE DOING Building and deploying production-grade machine learning software, tools and infrastructure. Developing reusable, scalable solutions to accelerate the delivery of ML systems. Operationalising machine learning models built using frameworks such as Scikit-learn, TensorFlow or PyTorch. Working across cloud platforms and infrastructure, including architecture and security considerations. Using Docker and Kubernetes to build, deploy and manage applications at scale. Contributing to technical scoping, software architecture and engineering best practices. Collaborating with software engineers, data scientists and commercial teams to solve complex client challenges. Advising customers and partners on technical approaches, translating complex concepts for non-technical stakeholders. Helping define standards and best practices for deploying machine learning systems at scale. WHAT I'M LOOKING FOR Strong Python development skills and a solid understanding of software engineering best practices. Experience taking machine learning models from development through to production. Understanding of the full machine learning lifecycle and experience operationalising models built with frameworks such as Scikit-learn, TensorFlow or PyTorch. Hands-on experience with cloud platforms such as AWS, Azure or GCP, including infrastructure, architecture and security. Experience with Docker and Kubernetes. A sound understanding of core machine learning concepts, including probability, statistics and common learning techniques. Strong communication skills, with the ability to advise technical teams and engage confidently with non-technical stakeholders. The ability to take ownership of technical scope, make informed decisions and deliver solutions in a fast-paced environment. Active UKSV DV clearance. THE OPPORTUNITY You'll join a team working at the intersection of software engineering and machine learning, helping bring ML systems into real-world use across critical client environments. This is a strong opportunity for a software engineer with hands-on ML deployment experience who enjoys solving complex technical problems, building scalable infrastructure and taking ownership of production-grade solutions.
Location: Crawley, United Kingdom Thales is a global technology leader with more than 83,000 employees on five continents. With over 7,500 people in the UK, operating across defence, space, aerospace, and digital security, we help build a future we can all trust. Thales supports the security and stability of our nation by providing extraordinary technology to our customers, as well as delivering social value to the UK with our products and services. DDCC Head of Engineering Crawley - Hybrid (Relocation support can be provided) About cortAIx and Thales: At Thales, we focus on building and delivering robust, real-world AI and Data solutions that make a tangible impact for our customers-and society at large. Our global cortAIx initiative unites over 600 AI and data specialists dedicated to developing trusted, operationally effective AI-powered systems for some of the most challenging and complex environments. In the UK, CortAIx is accelerating this mission by fostering technology, talent, and research focused on ethical, transparent, and explainable AI. Primary Purpose of the Role: DDCC is Thales UK's Digital and Data Competence Centre. This includes 3 primary areas of activity: cortAIx UK & Enterprise AI: Our AI incubation and industrialisation accelerator for deployed and enterprise AI solutions Data Enablement: Delivering foundational data tools, processes and architectures to support generation of value from data at pace Sovereign Cloud: Delivering cloud native platform solutions for Thales UK development and production activities The DDCC Head of Engineering role is focused on technical management of engineering activities primarily supporting cortAIx UK. They manage and monitor the solution engineering activities and the teams in terms of development process, practices and tools strategies across DDCC engineering activities What are we looking for: We're looking for an experienced Software Engineer who understands architecture and can provide cross functional leadership to a small, technical complex team to drive developments. This is very much a hands-on position, leading solution delivery by working with teams across Software, Systems, IVVQ, AI and Machine Learning. We need a solution provider, a force multiplier whose expertise sit in the delivery management of technical solutions but also can manage a small team of functional leaders and understands software architecture within safety critical environments. Due to the nature of the work, we require the successful individual to be able to hold UK EYES ONLY Security clearance. See below for further details. As DDCC Head of Engineering, your remit will cover: Stakeholder management: 1st point of contact for customer technical requirements/escalation points for scrum teams Governance: enforce technical direction; resolve cross-team conflicts. Talent development: hiring strategy, career ladders, mentoring systems, cross-discipline performance processes/escalation point. Change management: improving engineering effectiveness (e.g., test maturity, CI reliability, coding standards). Communication: translate leadership communication and analyse/describe impact to roadmap and trade-offs. Cross-team integration: coordinating platform, software, test/automation and support needs Quality, Safety, Cyber Assurance: verification strategy, traceability, defect management and Project Design Authority co-ordination/delivery Process/tooling: CI/CD for embedded, static analysis, unit/integration test frameworks, hardware-in-the-loop (HIL) testing, configuration management. Risk management: project technical risks reviews and management in conjunction AIDM Key Responsibilities and Tasks: Strategic Leadership Develop and execute the engineering strategy for AI products and platforms. Accountable for the technology roadmaps aligned to business objectives. Partner with executive leadership to identify and prioritise AI opportunities. Build a culture of innovation, experimentation, accountability, and continuous improvement. Act as a trusted advisor on emerging AI technologies, trends, and risks. Engineering Leadership Lead, coach, and develop Engineering Managers, Principal Engineers, AI Engineers and SW Engineers Build and scale high-performing, diverse engineering teams. Establish engineering standards, architecture principles, and delivery practices. Drive operational excellence across reliability, security, performance, and scalability. Foster a strong engineering culture focused on quality and customer outcomes. Operational Excellence Define the process for and track engineering metrics including but not limited to: Reliability Deployment frequency Lead time Platform utilisation Cost efficiency Drive automation throughout the software and AI lifecycle. Success Measures Within the first 12-24 months: Delivery of measurable business value from AI initiatives. Improved engineering productivity and deployment frequency High employee engagement and retention. Successful implementation of AI & Engineering governance frameworks. Core Skills and Experience required You will likely have academic qualifications in a relevant Engineering / Computer Science Discipline and will have experience among the following types of positions: Engineering Manager, Technical Project Manager, Software Engineering Manager, Technical Design Authority, Senior Systems / Solution Architecture roles in a relevant discipline You have worked on complex programmes in highly regulated environments /w defence / aerospace specific experience being of additional value You know how to verify the technical deliverables of engineering teams (customer needs, OCD, requirements, architecture choice ) You are able to lead and manage technical engineering projects, meeting the requirements with a clear view of the risks and opportunities You have significant experience in developing high quality technical documentation aligned to specified processes and frameworks You are able to engage and influence a diverse set of stakeholders as well as creating clear and achievable goals You are able to take decisions - even in uncertain contexts You are able to drive a culture of continuous improvement Experience of having delivered operational AI solutions into embedded environments would be advantageous or knowledge/qualifications/experience that suggest you can quickly learn tools and processes which enable the establishment and smooth running of an MLOps and AI delivery organisation in a complex environment Security Clearance Due the nature of the work that we do at Thales, many of our roles are subject to security restrictions. This role requires you to hold British Nationality, dual nationality can be considered. It would be advantageous if Security Clearance is currently held, however, if not currently held, it is a requirement that the successful applicant undergo, achieve, and maintain SC Clearance prior to commencing employment. Please visit the UKSV website for further guidance- United Kingdom Security Vetting - GOV.UK ( ) To be eligible for full SC, you generally need to have resided in the UK for the last 5 years. In some circumstances, a minimum of 3 years' residence in the UK over the last 5 years may be accepted, with additional overseas checks. Your Career at Thales UK Future opportunities will allow you to discover other domains or sites. You will be able to evolve and grow your Competencies in different areas: Room and attention to personal development Build your talents in another domain of Thales Group, discovering new products, new customers, new country or go to a more complex Solution Choose between a technical expertise or a leadership path Build an international career within a leading Engineering Group What we can offer We are committed to giving you opportunities to be your best. We believe in embracing the passion and potential of our people, and to achieve this we offer market leading training, development and experiences, along with the opportunity to be mentored and coached by some of the smartest minds in the industry. We hire from within as our first priority, so you'll have a myriad of opportunities within our diverse, global organisation. Our packages will include significant bonus, a strong pension contribution, private healthcare, development focused targets and relocation support can be provided if required along with a variety of learning, development and career enhancement opportunities. Further support can be provided towards academic and membership attainments. At Thales, we ensure equal opportunities, pay and working conditions for all. The benefits we offer include private medical insurance, buying or selling annual leave, cycle to work schemes, employee discounts, paid volunteering day, stocks and shares, annual bonus and much more depending on the role. Read more about our benefits here. We are committed to creating a workplace where everyone feels valued for who they are and the unique strengths they bring. Discover more about our programmes, employee networks, wellbeing policies, and inclusive features here click apply for full job details
Oct 22, 2026
Full time
Location: Crawley, United Kingdom Thales is a global technology leader with more than 83,000 employees on five continents. With over 7,500 people in the UK, operating across defence, space, aerospace, and digital security, we help build a future we can all trust. Thales supports the security and stability of our nation by providing extraordinary technology to our customers, as well as delivering social value to the UK with our products and services. DDCC Head of Engineering Crawley - Hybrid (Relocation support can be provided) About cortAIx and Thales: At Thales, we focus on building and delivering robust, real-world AI and Data solutions that make a tangible impact for our customers-and society at large. Our global cortAIx initiative unites over 600 AI and data specialists dedicated to developing trusted, operationally effective AI-powered systems for some of the most challenging and complex environments. In the UK, CortAIx is accelerating this mission by fostering technology, talent, and research focused on ethical, transparent, and explainable AI. Primary Purpose of the Role: DDCC is Thales UK's Digital and Data Competence Centre. This includes 3 primary areas of activity: cortAIx UK & Enterprise AI: Our AI incubation and industrialisation accelerator for deployed and enterprise AI solutions Data Enablement: Delivering foundational data tools, processes and architectures to support generation of value from data at pace Sovereign Cloud: Delivering cloud native platform solutions for Thales UK development and production activities The DDCC Head of Engineering role is focused on technical management of engineering activities primarily supporting cortAIx UK. They manage and monitor the solution engineering activities and the teams in terms of development process, practices and tools strategies across DDCC engineering activities What are we looking for: We're looking for an experienced Software Engineer who understands architecture and can provide cross functional leadership to a small, technical complex team to drive developments. This is very much a hands-on position, leading solution delivery by working with teams across Software, Systems, IVVQ, AI and Machine Learning. We need a solution provider, a force multiplier whose expertise sit in the delivery management of technical solutions but also can manage a small team of functional leaders and understands software architecture within safety critical environments. Due to the nature of the work, we require the successful individual to be able to hold UK EYES ONLY Security clearance. See below for further details. As DDCC Head of Engineering, your remit will cover: Stakeholder management: 1st point of contact for customer technical requirements/escalation points for scrum teams Governance: enforce technical direction; resolve cross-team conflicts. Talent development: hiring strategy, career ladders, mentoring systems, cross-discipline performance processes/escalation point. Change management: improving engineering effectiveness (e.g., test maturity, CI reliability, coding standards). Communication: translate leadership communication and analyse/describe impact to roadmap and trade-offs. Cross-team integration: coordinating platform, software, test/automation and support needs Quality, Safety, Cyber Assurance: verification strategy, traceability, defect management and Project Design Authority co-ordination/delivery Process/tooling: CI/CD for embedded, static analysis, unit/integration test frameworks, hardware-in-the-loop (HIL) testing, configuration management. Risk management: project technical risks reviews and management in conjunction AIDM Key Responsibilities and Tasks: Strategic Leadership Develop and execute the engineering strategy for AI products and platforms. Accountable for the technology roadmaps aligned to business objectives. Partner with executive leadership to identify and prioritise AI opportunities. Build a culture of innovation, experimentation, accountability, and continuous improvement. Act as a trusted advisor on emerging AI technologies, trends, and risks. Engineering Leadership Lead, coach, and develop Engineering Managers, Principal Engineers, AI Engineers and SW Engineers Build and scale high-performing, diverse engineering teams. Establish engineering standards, architecture principles, and delivery practices. Drive operational excellence across reliability, security, performance, and scalability. Foster a strong engineering culture focused on quality and customer outcomes. Operational Excellence Define the process for and track engineering metrics including but not limited to: Reliability Deployment frequency Lead time Platform utilisation Cost efficiency Drive automation throughout the software and AI lifecycle. Success Measures Within the first 12-24 months: Delivery of measurable business value from AI initiatives. Improved engineering productivity and deployment frequency High employee engagement and retention. Successful implementation of AI & Engineering governance frameworks. Core Skills and Experience required You will likely have academic qualifications in a relevant Engineering / Computer Science Discipline and will have experience among the following types of positions: Engineering Manager, Technical Project Manager, Software Engineering Manager, Technical Design Authority, Senior Systems / Solution Architecture roles in a relevant discipline You have worked on complex programmes in highly regulated environments /w defence / aerospace specific experience being of additional value You know how to verify the technical deliverables of engineering teams (customer needs, OCD, requirements, architecture choice ) You are able to lead and manage technical engineering projects, meeting the requirements with a clear view of the risks and opportunities You have significant experience in developing high quality technical documentation aligned to specified processes and frameworks You are able to engage and influence a diverse set of stakeholders as well as creating clear and achievable goals You are able to take decisions - even in uncertain contexts You are able to drive a culture of continuous improvement Experience of having delivered operational AI solutions into embedded environments would be advantageous or knowledge/qualifications/experience that suggest you can quickly learn tools and processes which enable the establishment and smooth running of an MLOps and AI delivery organisation in a complex environment Security Clearance Due the nature of the work that we do at Thales, many of our roles are subject to security restrictions. This role requires you to hold British Nationality, dual nationality can be considered. It would be advantageous if Security Clearance is currently held, however, if not currently held, it is a requirement that the successful applicant undergo, achieve, and maintain SC Clearance prior to commencing employment. Please visit the UKSV website for further guidance- United Kingdom Security Vetting - GOV.UK ( ) To be eligible for full SC, you generally need to have resided in the UK for the last 5 years. In some circumstances, a minimum of 3 years' residence in the UK over the last 5 years may be accepted, with additional overseas checks. Your Career at Thales UK Future opportunities will allow you to discover other domains or sites. You will be able to evolve and grow your Competencies in different areas: Room and attention to personal development Build your talents in another domain of Thales Group, discovering new products, new customers, new country or go to a more complex Solution Choose between a technical expertise or a leadership path Build an international career within a leading Engineering Group What we can offer We are committed to giving you opportunities to be your best. We believe in embracing the passion and potential of our people, and to achieve this we offer market leading training, development and experiences, along with the opportunity to be mentored and coached by some of the smartest minds in the industry. We hire from within as our first priority, so you'll have a myriad of opportunities within our diverse, global organisation. Our packages will include significant bonus, a strong pension contribution, private healthcare, development focused targets and relocation support can be provided if required along with a variety of learning, development and career enhancement opportunities. Further support can be provided towards academic and membership attainments. At Thales, we ensure equal opportunities, pay and working conditions for all. The benefits we offer include private medical insurance, buying or selling annual leave, cycle to work schemes, employee discounts, paid volunteering day, stocks and shares, annual bonus and much more depending on the role. Read more about our benefits here. We are committed to creating a workplace where everyone feels valued for who they are and the unique strengths they bring. Discover more about our programmes, employee networks, wellbeing policies, and inclusive features here click apply for full job details
Location: Glasgow, United Kingdom Thales is a global technology leader with more than 83,000 employees on five continents. With over 7,500 people in the UK, operating across defence, space, aerospace, and digital security, we help build a future we can all trust. Thales supports the security and stability of our nation by providing extraordinary technology to our customers, as well as delivering social value to the UK with our products and services. 2027 AI Engineer Apprentice - AI and Data Science Graduate Level Apprenticeship Start Date: 06 September 2027 Salary: £24,000 per annum Employee type: Permanent Location: Glasgow Working Schedule: Monday - Friday, 37 hours a week (8 hours Monday - Thursday, 5 hours Friday) Turn your curiosity into a career. If you're passionate about artificial intelligence, eager to learn, and looking for a degree apprenticeship that combines academic study with exciting on-the-job experience, we'd love to hear from you. Benefits of the programme: Earn a salary while studying for your qualification Gain hands-on experience in a real AI and engineering environment Receive job-specific training and development Achieve a recognised Level 6 qualification Secure a permanent role from the start of your apprenticeship Have your university tuition fees fully paid About the Role As an AI Engineer Apprentice, you will develop the technical knowledge, practical skills and professional behaviours needed to design, build, test and deploy dependable AI-enabled solutions. Working as part of our AI and engineering community, you will contribute to live projects across the machine learning lifecycle, collaborating with software, data, systems and domain specialists to turn needs into secure, maintainable solutions. Your responsibilities may include: Preparing, exploring and validating data for machine learning use cases Developing and evaluating machine learning models and AI-enabled software components Writing clean, tested and documented code using appropriate engineering tools and practices Supporting model integration, deployment, monitoring and performance improvement Contributing to technical reviews, experiments and structured problem solving Working with experienced engineers and researchers on live projects What You Will Learn Throughout the apprenticeship, you will gain experience and knowledge in: Professional engineering behaviours, teamwork and industry best practice Programming, software engineering, version control and automated testing Data preparation, feature engineering and data quality techniques Machine learning methods, model selection, training and evaluation Deployment patterns, MLOps, monitoring and lifecycle management Cloud, compute and development tools used to deliver AI solutions Responsible AI, security, privacy, safety and regulatory considerations Structured approaches to troubleshooting, experimentation and continuous improvement Degree Apprenticeship Programme You will study towards an AI and Data Science Graduate Level Apprenticeship qualification with Glasgow Caledonian University, developing the knowledge, skills and behaviours required to build and apply artificial intelligence responsibly in an engineering environment. The programme is delivered through a blended learning approach, combining: On campus study Live virtual lectures Online learning resources Self-directed study Programme structure: The BSc (Hons) AI and Data Science (Graduate Apprenticeship) will equip you with the knowledge and skills required to succeed in your role within Thales. Providing a strong foundation across data and AI, this programme will help you to learn how to manage, explore, analyse, understand and visualise data, alongside technical skills such as software development and machine learning. Delivered over 4 years, you will achieve: Year 1: Certificate of Higher Education in Computing Year 2: Diploma of Higher Education in Computing Year 4: BSc (Hons) AI and Data Science (Graduate Apprenticeship) Entry Requirements To apply, you will need: Highers 96 UCAS points Four Highers (BBCC) including Maths or Computing A foundation apprenticeship will be equal to one Higher at B A modern apprenticeship SCQF Level 6 in a relevant discipline will be equal to two Highers at B Benefits Competitive salary of £24,000 per annum Performance-related pay uplifts Holiday entitlement of 201 hours a year (plus a company day and bank holidays) Contributory Company Pension Health Care Cash Plan Hybrid/flexible working options Employee assistance programme Learning and development support Employee discounts and wellbeing initiatives Life Cover 80 Hours Volunteering per year (first two years) Thales Apprentice Recruitment Process 1. Apply Online - submit your application online to register your interest. You only need to register for one role as you will have the opportunity to apply for additional roles at the full application stage. 2. Upload Your CV 3. Check your emails for the invitation to apply - this will comefrom 4. Complete Your Application - follow the link provided in the email to complete your application. You can apply for one primary role and up to 3 additional roles. 5. Complete Online Tests - undertake the online assessments designed to evaluate your suitability for the role. 6. Virtual Assessment Centre - candidates who progress from the online assessment stage will attend a virtual assessment centre, which will include group exercises, and competency-based interviews. 7. Job Offer - successful candidates who perform well throughout the recruitment process will receive a job offer from Thales. For further information about our Future Talent recruitment process, including hints and tips, or to connect with a member of the Future Talent Team, a Graduate, or an Apprentice, please visit Thales Future Talent - Connectr . Please note, assessment centres for shortlisted candidates will be held between February - May 2027. Induction week for all Graduate and Apprentices will take place from Monday 6 September - Friday 10 September 2027. Closing date: Our applications will close at 11.59pm on Wednesday 17 February 2027, this is the only time we will be accepting applications this year. Please note, we will be in contact by the end of February 2027 with details of next steps. PLEASE NOTE THAT ROLES MAY CLOSE EARLIER THAN THE ADVERTISED DEADLINE IF WE RECEIVE A HIGH NUMER OF APPLICATIONS. WE ENCOURAGE YOU TO APPLY AS SOON AS POSSIBLE TO AVOID MISSING OUT ON THIS OPPORTUNITY. Because of the work we do at Thales, all roles are subject to security requirements. To be considered for this position, you must have the permanent right to work in the UK and be able to successfully complete and maintain UK Government security checks, including Baseline Personnel Security Standard (BPSS) screening and Security Clearance (SC), which is a government background check, before starting employment. To be eligible for SC clearance, you will typically need to have lived in the UK continuously for the last five years. As part of the vetting process, you will be asked to provide evidence of your identity, right to work in the UK, any time spent overseas during the last five years, and your employment and/or education history. For further details of the evidence required to apply for security clearance please follow this link - . Thales is an equal opportunities employer and diversity, and inclusion are integral to the success of Thales. At Thales, we ensure equal opportunities, pay and working conditions for all. The benefits we offer include private medical insurance, buying or selling annual leave, cycle to work schemes, employee discounts, paid volunteering day, stocks and shares, annual bonus and much more depending on the role. Read more about our benefits here. We are committed to creating a workplace where everyone feels valued for who they are and the unique strengths they bring. Discover more about our programmes, employee networks, wellbeing policies, and inclusive features here. If this role isn't quite right for you, we encourage you to join our talent community where your details will be shared with our recruitment teams for other potential opportunities. Join the Talent Community here. Join Thales in the UK - Innovate with us and shape the future!
Oct 22, 2026
Full time
Location: Glasgow, United Kingdom Thales is a global technology leader with more than 83,000 employees on five continents. With over 7,500 people in the UK, operating across defence, space, aerospace, and digital security, we help build a future we can all trust. Thales supports the security and stability of our nation by providing extraordinary technology to our customers, as well as delivering social value to the UK with our products and services. 2027 AI Engineer Apprentice - AI and Data Science Graduate Level Apprenticeship Start Date: 06 September 2027 Salary: £24,000 per annum Employee type: Permanent Location: Glasgow Working Schedule: Monday - Friday, 37 hours a week (8 hours Monday - Thursday, 5 hours Friday) Turn your curiosity into a career. If you're passionate about artificial intelligence, eager to learn, and looking for a degree apprenticeship that combines academic study with exciting on-the-job experience, we'd love to hear from you. Benefits of the programme: Earn a salary while studying for your qualification Gain hands-on experience in a real AI and engineering environment Receive job-specific training and development Achieve a recognised Level 6 qualification Secure a permanent role from the start of your apprenticeship Have your university tuition fees fully paid About the Role As an AI Engineer Apprentice, you will develop the technical knowledge, practical skills and professional behaviours needed to design, build, test and deploy dependable AI-enabled solutions. Working as part of our AI and engineering community, you will contribute to live projects across the machine learning lifecycle, collaborating with software, data, systems and domain specialists to turn needs into secure, maintainable solutions. Your responsibilities may include: Preparing, exploring and validating data for machine learning use cases Developing and evaluating machine learning models and AI-enabled software components Writing clean, tested and documented code using appropriate engineering tools and practices Supporting model integration, deployment, monitoring and performance improvement Contributing to technical reviews, experiments and structured problem solving Working with experienced engineers and researchers on live projects What You Will Learn Throughout the apprenticeship, you will gain experience and knowledge in: Professional engineering behaviours, teamwork and industry best practice Programming, software engineering, version control and automated testing Data preparation, feature engineering and data quality techniques Machine learning methods, model selection, training and evaluation Deployment patterns, MLOps, monitoring and lifecycle management Cloud, compute and development tools used to deliver AI solutions Responsible AI, security, privacy, safety and regulatory considerations Structured approaches to troubleshooting, experimentation and continuous improvement Degree Apprenticeship Programme You will study towards an AI and Data Science Graduate Level Apprenticeship qualification with Glasgow Caledonian University, developing the knowledge, skills and behaviours required to build and apply artificial intelligence responsibly in an engineering environment. The programme is delivered through a blended learning approach, combining: On campus study Live virtual lectures Online learning resources Self-directed study Programme structure: The BSc (Hons) AI and Data Science (Graduate Apprenticeship) will equip you with the knowledge and skills required to succeed in your role within Thales. Providing a strong foundation across data and AI, this programme will help you to learn how to manage, explore, analyse, understand and visualise data, alongside technical skills such as software development and machine learning. Delivered over 4 years, you will achieve: Year 1: Certificate of Higher Education in Computing Year 2: Diploma of Higher Education in Computing Year 4: BSc (Hons) AI and Data Science (Graduate Apprenticeship) Entry Requirements To apply, you will need: Highers 96 UCAS points Four Highers (BBCC) including Maths or Computing A foundation apprenticeship will be equal to one Higher at B A modern apprenticeship SCQF Level 6 in a relevant discipline will be equal to two Highers at B Benefits Competitive salary of £24,000 per annum Performance-related pay uplifts Holiday entitlement of 201 hours a year (plus a company day and bank holidays) Contributory Company Pension Health Care Cash Plan Hybrid/flexible working options Employee assistance programme Learning and development support Employee discounts and wellbeing initiatives Life Cover 80 Hours Volunteering per year (first two years) Thales Apprentice Recruitment Process 1. Apply Online - submit your application online to register your interest. You only need to register for one role as you will have the opportunity to apply for additional roles at the full application stage. 2. Upload Your CV 3. Check your emails for the invitation to apply - this will comefrom 4. Complete Your Application - follow the link provided in the email to complete your application. You can apply for one primary role and up to 3 additional roles. 5. Complete Online Tests - undertake the online assessments designed to evaluate your suitability for the role. 6. Virtual Assessment Centre - candidates who progress from the online assessment stage will attend a virtual assessment centre, which will include group exercises, and competency-based interviews. 7. Job Offer - successful candidates who perform well throughout the recruitment process will receive a job offer from Thales. For further information about our Future Talent recruitment process, including hints and tips, or to connect with a member of the Future Talent Team, a Graduate, or an Apprentice, please visit Thales Future Talent - Connectr . Please note, assessment centres for shortlisted candidates will be held between February - May 2027. Induction week for all Graduate and Apprentices will take place from Monday 6 September - Friday 10 September 2027. Closing date: Our applications will close at 11.59pm on Wednesday 17 February 2027, this is the only time we will be accepting applications this year. Please note, we will be in contact by the end of February 2027 with details of next steps. PLEASE NOTE THAT ROLES MAY CLOSE EARLIER THAN THE ADVERTISED DEADLINE IF WE RECEIVE A HIGH NUMER OF APPLICATIONS. WE ENCOURAGE YOU TO APPLY AS SOON AS POSSIBLE TO AVOID MISSING OUT ON THIS OPPORTUNITY. Because of the work we do at Thales, all roles are subject to security requirements. To be considered for this position, you must have the permanent right to work in the UK and be able to successfully complete and maintain UK Government security checks, including Baseline Personnel Security Standard (BPSS) screening and Security Clearance (SC), which is a government background check, before starting employment. To be eligible for SC clearance, you will typically need to have lived in the UK continuously for the last five years. As part of the vetting process, you will be asked to provide evidence of your identity, right to work in the UK, any time spent overseas during the last five years, and your employment and/or education history. For further details of the evidence required to apply for security clearance please follow this link - . Thales is an equal opportunities employer and diversity, and inclusion are integral to the success of Thales. At Thales, we ensure equal opportunities, pay and working conditions for all. The benefits we offer include private medical insurance, buying or selling annual leave, cycle to work schemes, employee discounts, paid volunteering day, stocks and shares, annual bonus and much more depending on the role. Read more about our benefits here. We are committed to creating a workplace where everyone feels valued for who they are and the unique strengths they bring. Discover more about our programmes, employee networks, wellbeing policies, and inclusive features here. If this role isn't quite right for you, we encourage you to join our talent community where your details will be shared with our recruitment teams for other potential opportunities. Join the Talent Community here. Join Thales in the UK - Innovate with us and shape the future!
Description With 49,000 colleagues in over 140 countries, we help organisations make forward-thinking choices about their people, their investments and the risks they face. Joining our Insurance Consulting and Technology (ICT) team, you'll be part of our impact right from the start. Our ICT team combines deep consulting expertise with innovative technology to develop cutting-edge solutions for the global insurance industry. The market-leading risk and financial modelling software we develop is used by over 1,000 clients across six continents. Our 1,700 ICT colleagues in 35 markets share one mission - to innovate and transform insurance. To make this a reality, we deliver solutions that help our clients better select, finance and manage risk and capital. We develop software solutions that support insurance companies and other businesses that require sophisticated machine modelling and analytics processes as they confront volatile markets and regulatory changes. Our work underpins complex financial activities ranging from asset-liability modelling, pricing and reserving to economic capital aggregation and allocation. At WTW, we believe difference makes us stronger. We want our workforce to reflect the different and varied markets we operate in and to build a culture of inclusivity that makes colleagues feel welcome, valued and empowered to bring their whole selves to work every day. We are an equal opportunity employer committed to fostering an inclusive work environment throughout our organisation. We embrace all types of diversity. Responsibilities: Joining us for eight weeks, you'll build invaluable real-world experience at the heart of our Insurance Technology business. You'll work with and learn from our industry-leading experts, while: Experiencing our collaborative and innovative approach to engineering Contributing to a business-applicable project that covers a wide range of software delivery technologies and processes Taking on more responsibilities as you grow, in areas such as performance benchmarking, testing, DevOps and security Gaining hands-on experience with Generative AI tools and techniques, learning how you can support software engineering activities while developing the critical thinking skills needed to evaluate, validate and apply AI-generated outputs effectively and responsibly Presenting your work and findings to colleagues and your fellow interns Learning every day with the support of your colleagues and dedicated mentors This is the perfect opportunity to understand what you could expect if you joined our graduate programme the following year; those who perform well during the internship may be offered a permanent graduate role. Qualifications Requirements: To transform your tomorrow with a WTW internship, you'll need to be: In your penultimate year at university and on course to achieve a 2:1 degree in a technical, analytical or mathematical discipline You'll need an A in Maths and an A in two further subjects at A Level or equivalent Aware of a software development language, such as C#, C++, Java or Python, and web technologies such as HTML/CSS or JavaScript Familiar with the basic principles of software development Genuinely interested in current and emerging technologies A natural problem solver with a mathematical and analytical mind Good at communicating and working as part of a team Eager to gain and apply new knowledge Closing Date: 15th November 2026 Please note that we do not accept multiple applications and you should only select and apply to one programme per year Workstyles: We believe in the value of in-person learning at this early stage of your career, so you'll be expected to come into the office at least three days a week. The Application Process: Stage 1: Apply online and attach your CV Stage 2: Complete an online test and video interview Stage 3: Showcase your coding skills in an online coding assessment Stage 4: A virtual assessment centre, where you'll get to meet members of the team Stage 5: Offer and onboarding We're committed to equal employment opportunity and provide application, interview and workplace adjustments and accommodations to all applicants. If you foresee any barriers, from the application process through to joining WTW, please email We are committed to maintaining a fair and equitable process for all candidates - read our AI Guidance .
Oct 22, 2026
Full time
Description With 49,000 colleagues in over 140 countries, we help organisations make forward-thinking choices about their people, their investments and the risks they face. Joining our Insurance Consulting and Technology (ICT) team, you'll be part of our impact right from the start. Our ICT team combines deep consulting expertise with innovative technology to develop cutting-edge solutions for the global insurance industry. The market-leading risk and financial modelling software we develop is used by over 1,000 clients across six continents. Our 1,700 ICT colleagues in 35 markets share one mission - to innovate and transform insurance. To make this a reality, we deliver solutions that help our clients better select, finance and manage risk and capital. We develop software solutions that support insurance companies and other businesses that require sophisticated machine modelling and analytics processes as they confront volatile markets and regulatory changes. Our work underpins complex financial activities ranging from asset-liability modelling, pricing and reserving to economic capital aggregation and allocation. At WTW, we believe difference makes us stronger. We want our workforce to reflect the different and varied markets we operate in and to build a culture of inclusivity that makes colleagues feel welcome, valued and empowered to bring their whole selves to work every day. We are an equal opportunity employer committed to fostering an inclusive work environment throughout our organisation. We embrace all types of diversity. Responsibilities: Joining us for eight weeks, you'll build invaluable real-world experience at the heart of our Insurance Technology business. You'll work with and learn from our industry-leading experts, while: Experiencing our collaborative and innovative approach to engineering Contributing to a business-applicable project that covers a wide range of software delivery technologies and processes Taking on more responsibilities as you grow, in areas such as performance benchmarking, testing, DevOps and security Gaining hands-on experience with Generative AI tools and techniques, learning how you can support software engineering activities while developing the critical thinking skills needed to evaluate, validate and apply AI-generated outputs effectively and responsibly Presenting your work and findings to colleagues and your fellow interns Learning every day with the support of your colleagues and dedicated mentors This is the perfect opportunity to understand what you could expect if you joined our graduate programme the following year; those who perform well during the internship may be offered a permanent graduate role. Qualifications Requirements: To transform your tomorrow with a WTW internship, you'll need to be: In your penultimate year at university and on course to achieve a 2:1 degree in a technical, analytical or mathematical discipline You'll need an A in Maths and an A in two further subjects at A Level or equivalent Aware of a software development language, such as C#, C++, Java or Python, and web technologies such as HTML/CSS or JavaScript Familiar with the basic principles of software development Genuinely interested in current and emerging technologies A natural problem solver with a mathematical and analytical mind Good at communicating and working as part of a team Eager to gain and apply new knowledge Closing Date: 15th November 2026 Please note that we do not accept multiple applications and you should only select and apply to one programme per year Workstyles: We believe in the value of in-person learning at this early stage of your career, so you'll be expected to come into the office at least three days a week. The Application Process: Stage 1: Apply online and attach your CV Stage 2: Complete an online test and video interview Stage 3: Showcase your coding skills in an online coding assessment Stage 4: A virtual assessment centre, where you'll get to meet members of the team Stage 5: Offer and onboarding We're committed to equal employment opportunity and provide application, interview and workplace adjustments and accommodations to all applicants. If you foresee any barriers, from the application process through to joining WTW, please email We are committed to maintaining a fair and equitable process for all candidates - read our AI Guidance .
Job Title Data Scientist Job Description Job purpose: Our IT mission is to transform how data and AI are delivered to customers and colleagues around the world, with a focus on simplicity, trust, and measurable value. AI is central to this mission, providing tools and platforms for creating and operating secure, scalable data and AI solutions. Reporting to the BI and Analytics Manager, the Data Scientist is a valued member of the Enterprise Analytics & AI Hub. This role develops and evaluates advanced analytics, machine learning, and generative AI solutions that help us understand business challenges, improve decisions, and create better customer and colleague experiences. Using modern data science techniques and scalable AWS technologies, the Data Scientist connects business needs with reliable technical solutions. This role works closely with product, data engineering, software and platform engineering, security, governance, and domain experts to move ideas from discovery and experimentation into monitored production services. The Data Scientist plays a vital role within the Enterprise Analytics & AI Hub, contributing to the team's core objectives: • Turn ambiguous business questions into measurable data science problems, clear success measures, and evidence-based recommendations. • Build trusted models, data products, and AI capabilities in Nexus (our internal platform) that colleagues can use safely and effectively. • Improve the quality and usability of structured and unstructured data by making definitions, lineage, assumptions, and limitations clear. • Establish evaluation, observability, and feedback practices that improve accuracy, reliability, latency, and cost over time. • Foster a culture of responsible, data-informed experimentation by sharing insights, reusable approaches, and emerging techniques across the team. Key Responsibilities Key Responsibilities: Partner with product owners, domain experts, and stakeholders to translate business challenges into measurable analytical or AI outcomes, data requirements, and evaluation plans. Explore, prepare, and validate structured and unstructured data, establishing appropriate quality checks, feature definitions, lineage, and documented limitations. Design, develop, and validate statistical and machine learning solutions for tasks such as classification, regression, clustering, forecasting, segmentation, and optimization. Design experiments and apply statistical analysis, including A/B testing where appropriate, to measure impact, interpret uncertainty, and support sound decisions. Build and evaluate generative AI capabilities within Nexus (AWS stack), including prompt and context design, embeddings, retrieval-augmented generation, knowledge bases, and agent or tool behaviours. Write production-quality Python and SQL, and work with engineers to integrate successful solutions into scalable AWS services, data pipelines, and APIs. Apply MLOps and LLMOps practices, including version control, automated tests, CI/CD, reproducible deployment, monitoring, drift detection, and rollback. Define and maintain offline and live evaluation measures, using traces, token usage, cost, performance, and user feedback to improve solutions over time. Apply responsible AI, privacy, security, and data governance principles, with appropriate access controls, explainability, safety checks, and human oversight. Communicate insights, trade-offs, and recommendations clearly to technical and business audiences, and contribute reusable patterns, documentation, and learning across the team. Function IT Country United Kingdom Office Location Newcastle Work Place type Hybrid Advert Working at Sage means you're supporting millions of small and medium sized businesses globally with technology to work faster and smarter. We leverage the future of AI, meaning business owners spend less time doing routine tasks, like entering invoices and generating reports, and more time pursuing their ambitions. Our colleagues are the best of the best. It's why we were awarded 2024 Best Places to Work by Glassdoor. Because to achieve extraordinary outcomes, we need extraordinary teams. This means infusing Sage with people who knock down barriers, continuously innovate, and want to experience their potential. Learn more about working at Sage: Watch a video about our culture: v=qIoiCpZH-QE We celebrate individuality and welcome you to join us if you embrace all backgrounds, identities, beliefs, and ways of working. If you need support applying, reach out at . Learn more about DEI at Sage:
Oct 22, 2026
Full time
Job Title Data Scientist Job Description Job purpose: Our IT mission is to transform how data and AI are delivered to customers and colleagues around the world, with a focus on simplicity, trust, and measurable value. AI is central to this mission, providing tools and platforms for creating and operating secure, scalable data and AI solutions. Reporting to the BI and Analytics Manager, the Data Scientist is a valued member of the Enterprise Analytics & AI Hub. This role develops and evaluates advanced analytics, machine learning, and generative AI solutions that help us understand business challenges, improve decisions, and create better customer and colleague experiences. Using modern data science techniques and scalable AWS technologies, the Data Scientist connects business needs with reliable technical solutions. This role works closely with product, data engineering, software and platform engineering, security, governance, and domain experts to move ideas from discovery and experimentation into monitored production services. The Data Scientist plays a vital role within the Enterprise Analytics & AI Hub, contributing to the team's core objectives: • Turn ambiguous business questions into measurable data science problems, clear success measures, and evidence-based recommendations. • Build trusted models, data products, and AI capabilities in Nexus (our internal platform) that colleagues can use safely and effectively. • Improve the quality and usability of structured and unstructured data by making definitions, lineage, assumptions, and limitations clear. • Establish evaluation, observability, and feedback practices that improve accuracy, reliability, latency, and cost over time. • Foster a culture of responsible, data-informed experimentation by sharing insights, reusable approaches, and emerging techniques across the team. Key Responsibilities Key Responsibilities: Partner with product owners, domain experts, and stakeholders to translate business challenges into measurable analytical or AI outcomes, data requirements, and evaluation plans. Explore, prepare, and validate structured and unstructured data, establishing appropriate quality checks, feature definitions, lineage, and documented limitations. Design, develop, and validate statistical and machine learning solutions for tasks such as classification, regression, clustering, forecasting, segmentation, and optimization. Design experiments and apply statistical analysis, including A/B testing where appropriate, to measure impact, interpret uncertainty, and support sound decisions. Build and evaluate generative AI capabilities within Nexus (AWS stack), including prompt and context design, embeddings, retrieval-augmented generation, knowledge bases, and agent or tool behaviours. Write production-quality Python and SQL, and work with engineers to integrate successful solutions into scalable AWS services, data pipelines, and APIs. Apply MLOps and LLMOps practices, including version control, automated tests, CI/CD, reproducible deployment, monitoring, drift detection, and rollback. Define and maintain offline and live evaluation measures, using traces, token usage, cost, performance, and user feedback to improve solutions over time. Apply responsible AI, privacy, security, and data governance principles, with appropriate access controls, explainability, safety checks, and human oversight. Communicate insights, trade-offs, and recommendations clearly to technical and business audiences, and contribute reusable patterns, documentation, and learning across the team. Function IT Country United Kingdom Office Location Newcastle Work Place type Hybrid Advert Working at Sage means you're supporting millions of small and medium sized businesses globally with technology to work faster and smarter. We leverage the future of AI, meaning business owners spend less time doing routine tasks, like entering invoices and generating reports, and more time pursuing their ambitions. Our colleagues are the best of the best. It's why we were awarded 2024 Best Places to Work by Glassdoor. Because to achieve extraordinary outcomes, we need extraordinary teams. This means infusing Sage with people who knock down barriers, continuously innovate, and want to experience their potential. Learn more about working at Sage: Watch a video about our culture: v=qIoiCpZH-QE We celebrate individuality and welcome you to join us if you embrace all backgrounds, identities, beliefs, and ways of working. If you need support applying, reach out at . Learn more about DEI at Sage:
Location: Reading, United Kingdom Thales is a global technology leader with more than 83,000 employees on five continents. With over 7,500 people in the UK, operating across defence, space, aerospace, and digital security, we help build a future we can all trust. Thales supports the security and stability of our nation by providing extraordinary technology to our customers, as well as delivering social value to the UK with our products and services. AI Researcher Reading (RG2 6GF) - Hybrid Primary Purpose of the Role: To conduct high-impact AI research that develops novel, trustworthy and operationally relevant AI capabilities across Thales UK businesses and for our customers, increasing the quality of our offers, winning new business, strengthening technical differentiation, and improving customer outcomes. As part of the growing software, AI and research capability in cortAIx Factory / cortAIx UK, the AI Researcher will collaborate with AI engineers, AI assurance specialists, human-machine teaming researchers, product owners, domain experts, data engineers and software engineers to turn complex operational and business challenges into validated AI research outcomes, proofs of concept and transferable technical capability. The role will contribute novel AI methods, research assets, technical reports, publications, invention disclosures and reusable experimental approaches to Thales UK's internal catalogue of capabilities, accelerating responsible AI adoption across programmes. The role will connect with data, digital, research and engineering specialists across Thales UK and Group, maturing emerging AI technologies for future deployment and acting as a technical expert on advanced AI research used transversally throughout the business. We are interested in people with a background of both conduct research and delivering across a diverse range of products or industries. We are looking for those who can undertake the research but also understand how to translate this into product. Highly advantageous if you've supported or led bids/bid requirements. Key Responsibilities and Tasks: Conduct applied and experimental AI research to solve complex customer and business problems across defence, aerospace, cyber security, rail, critical national infrastructure and related domains. Develop state-of-the-art AI/ML solutions, proofs of concept and research prototypes using real-world data and operationally relevant problem statements. Investigate, design, implement and evaluate advanced AI methods, including but not limited to deep learning, multimodal AI, self-supervised learning, foundation models, generative AI, computer vision, NLP/LLMs, time-series analytics and reinforcement learning where relevant. Translate business and customer needs into clear research questions, experimental plans, technical requirements and measurable success criteria. Design robust evaluation methodologies, including baselines, benchmarks, ablation studies, uncertainty assessment, robustness testing and performance measurement against operationally meaningful metrics. Collaborate with AI V&V, AI Assurance, Human-Machine Teaming and Applied AI groups to ensure research outputs are trustworthy, human-centred, explainable and suitable for future operational use. Build reproducible research pipelines, including data preprocessing, feature engineering, model training, experiment tracking, evaluation and technical reporting. Ensure Responsible AI practices are embedded throughout the research lifecycle, including robustness, safety, explainability, transparency, fairness, privacy, security and alignment with MOD, regulatory and Thales governance requirements. Create proofs of concept, publications, invention disclosures, patents, technical reports and reusable research assets around advanced AI topics such as multimodal learning, self-supervised learning, foundation models and human-AI collaboration. Package research outputs in a form that enables transition to AI engineering teams, including demonstrator code, model cards, experiment reports, design notes and handover documentation. Support bids, PoCs, demos, customer workshops, innovation campaigns and stakeholder briefings by communicating research concepts and outcomes to technical and non-technical audiences. Work with data engineers, architects and domain experts on data acquisition, labelling strategies, synthetic data approaches, integration of third-party data and data quality management. Horizon scan for major AI research and technology trends, assess relevance to Thales markets, run trials and share best practices to accelerate responsible adoption. Skills, experience and qualifications required Degree/Masters, an equivalent in a relevant Software/AI subject, or equivalent experience. Relevant subject areas may include Artificial Intelligence, Machine Learning, Computer Science, Data Science, Mathematics, Engineering, Physics or a related technical discipline. Strong Python programming skills; proficiency with modern software engineering and research practices, including testing, code quality, reproducibility and collaborative development. Experience conducting AI/ML research or advanced AI development in complex technical environments, preferably including defence, aviation, rail, cyber security, safety-critical, mission-critical or similarly regulated domains. Expertise in ML/DL algorithms and techniques for supervised, unsupervised, self-supervised and, where relevant, reinforcement learning. Proven ability to take AI research from problem framing through experimental design, model development, evaluation and prototype demonstration. Hands-on experience in at least one advanced AI area such as deep neural networks, computer vision, NLP/LLMs, multimodal AI, self-supervised learning, reinforcement learning, time-series analytics or foundation models. Experience with AI frameworks and libraries: PyTorch, TensorFlow, scikit-learn, Hugging Face Transformers; OpenCV for vision applications. Strong understanding of experimental design, statistical evaluation, benchmarking and model validation. Experiment tracking and reproducibility tools, for example MLflow, Weights & Biases or equivalent. Data wrangling and analysis using Pandas, NumPy, SQL; familiarity with Spark or similar is a plus. Model optimisation and research-to-prototype deployment fundamentals, including ONNX, TorchScript, FastAPI/gRPC and GPU acceleration, with CUDA basics desirable. Responsible AI and security awareness: explainability, privacy-preserving methods, bias assessment, safety, assurance, adversarial robustness and secure AI. Scientific and technical writing skills, including preparation of technical reports, research papers, invention disclosures, model cards and experiment reports. Demonstrable experience producing high-quality technical documentation, research outputs, model evaluations or stakeholder briefings. Interpersonal Skills Ability to engage and influence diverse stakeholders, including Product Engineering Leaders, Customers, Design Authorities, Project Management, IS/IT, research partners and academic collaborators. Highly effective in a matrix-based organisation; a collaborative team player who drives outcomes while maintaining scientific rigour. Excellent communication skills; able to explain complex AI research concepts clearly to technical and non-technical audiences. Curious, creative and intellectually rigorous, with the ability to challenge constructively and develop novel solutions to ambiguous problems. Encourages an open environment where ideas are shared, technical debate is welcomed and innovation thrives. Desirable PhD or equivalent research experience in Artificial Intelligence, Machine Learning, Computer Science, Mathematics, Engineering, Physics or a related discipline. Peer-reviewed publications, patents, invention disclosures, open-source contributions or recognised technical innovations. Experience with governance of architecture, research designs or detailed technical designs throughout the project lifecycle. Experience with large-scale data initiatives, data labelling strategies, synthetic data generation and data quality management. Familiarity with MLOps practices and cloud platforms for AI deployment. Experience working with academic partners, research institutions, grant-funded programmes or collaborative research consortia. Experience contributing to bids, proposals, customer demonstrations or externally funded innovation activities. Knowledge of cloud AI services, HPC environments, containerisation and secure research environments is desirable. Security Clearance statement Due the nature of the work that we do at Thales, many of our roles are subject to security restrictions. This role requires you to be a sole British National and achieve Security Clearance (SC) without any caveats. It would be advantageous if currently held, however, if not currently held, it is a requirement that the successful applicant undergo, achieve, and maintain SC Clearance prior to commencing employment. Please visit the UKSV website for further guidance- United Kingdom Security Vetting - GOV.UK ( ) To be eligible for full SC, you generally need to have resided in the UK for the last 5 years. In some circumstances . click apply for full job details
Oct 22, 2026
Full time
Location: Reading, United Kingdom Thales is a global technology leader with more than 83,000 employees on five continents. With over 7,500 people in the UK, operating across defence, space, aerospace, and digital security, we help build a future we can all trust. Thales supports the security and stability of our nation by providing extraordinary technology to our customers, as well as delivering social value to the UK with our products and services. AI Researcher Reading (RG2 6GF) - Hybrid Primary Purpose of the Role: To conduct high-impact AI research that develops novel, trustworthy and operationally relevant AI capabilities across Thales UK businesses and for our customers, increasing the quality of our offers, winning new business, strengthening technical differentiation, and improving customer outcomes. As part of the growing software, AI and research capability in cortAIx Factory / cortAIx UK, the AI Researcher will collaborate with AI engineers, AI assurance specialists, human-machine teaming researchers, product owners, domain experts, data engineers and software engineers to turn complex operational and business challenges into validated AI research outcomes, proofs of concept and transferable technical capability. The role will contribute novel AI methods, research assets, technical reports, publications, invention disclosures and reusable experimental approaches to Thales UK's internal catalogue of capabilities, accelerating responsible AI adoption across programmes. The role will connect with data, digital, research and engineering specialists across Thales UK and Group, maturing emerging AI technologies for future deployment and acting as a technical expert on advanced AI research used transversally throughout the business. We are interested in people with a background of both conduct research and delivering across a diverse range of products or industries. We are looking for those who can undertake the research but also understand how to translate this into product. Highly advantageous if you've supported or led bids/bid requirements. Key Responsibilities and Tasks: Conduct applied and experimental AI research to solve complex customer and business problems across defence, aerospace, cyber security, rail, critical national infrastructure and related domains. Develop state-of-the-art AI/ML solutions, proofs of concept and research prototypes using real-world data and operationally relevant problem statements. Investigate, design, implement and evaluate advanced AI methods, including but not limited to deep learning, multimodal AI, self-supervised learning, foundation models, generative AI, computer vision, NLP/LLMs, time-series analytics and reinforcement learning where relevant. Translate business and customer needs into clear research questions, experimental plans, technical requirements and measurable success criteria. Design robust evaluation methodologies, including baselines, benchmarks, ablation studies, uncertainty assessment, robustness testing and performance measurement against operationally meaningful metrics. Collaborate with AI V&V, AI Assurance, Human-Machine Teaming and Applied AI groups to ensure research outputs are trustworthy, human-centred, explainable and suitable for future operational use. Build reproducible research pipelines, including data preprocessing, feature engineering, model training, experiment tracking, evaluation and technical reporting. Ensure Responsible AI practices are embedded throughout the research lifecycle, including robustness, safety, explainability, transparency, fairness, privacy, security and alignment with MOD, regulatory and Thales governance requirements. Create proofs of concept, publications, invention disclosures, patents, technical reports and reusable research assets around advanced AI topics such as multimodal learning, self-supervised learning, foundation models and human-AI collaboration. Package research outputs in a form that enables transition to AI engineering teams, including demonstrator code, model cards, experiment reports, design notes and handover documentation. Support bids, PoCs, demos, customer workshops, innovation campaigns and stakeholder briefings by communicating research concepts and outcomes to technical and non-technical audiences. Work with data engineers, architects and domain experts on data acquisition, labelling strategies, synthetic data approaches, integration of third-party data and data quality management. Horizon scan for major AI research and technology trends, assess relevance to Thales markets, run trials and share best practices to accelerate responsible adoption. Skills, experience and qualifications required Degree/Masters, an equivalent in a relevant Software/AI subject, or equivalent experience. Relevant subject areas may include Artificial Intelligence, Machine Learning, Computer Science, Data Science, Mathematics, Engineering, Physics or a related technical discipline. Strong Python programming skills; proficiency with modern software engineering and research practices, including testing, code quality, reproducibility and collaborative development. Experience conducting AI/ML research or advanced AI development in complex technical environments, preferably including defence, aviation, rail, cyber security, safety-critical, mission-critical or similarly regulated domains. Expertise in ML/DL algorithms and techniques for supervised, unsupervised, self-supervised and, where relevant, reinforcement learning. Proven ability to take AI research from problem framing through experimental design, model development, evaluation and prototype demonstration. Hands-on experience in at least one advanced AI area such as deep neural networks, computer vision, NLP/LLMs, multimodal AI, self-supervised learning, reinforcement learning, time-series analytics or foundation models. Experience with AI frameworks and libraries: PyTorch, TensorFlow, scikit-learn, Hugging Face Transformers; OpenCV for vision applications. Strong understanding of experimental design, statistical evaluation, benchmarking and model validation. Experiment tracking and reproducibility tools, for example MLflow, Weights & Biases or equivalent. Data wrangling and analysis using Pandas, NumPy, SQL; familiarity with Spark or similar is a plus. Model optimisation and research-to-prototype deployment fundamentals, including ONNX, TorchScript, FastAPI/gRPC and GPU acceleration, with CUDA basics desirable. Responsible AI and security awareness: explainability, privacy-preserving methods, bias assessment, safety, assurance, adversarial robustness and secure AI. Scientific and technical writing skills, including preparation of technical reports, research papers, invention disclosures, model cards and experiment reports. Demonstrable experience producing high-quality technical documentation, research outputs, model evaluations or stakeholder briefings. Interpersonal Skills Ability to engage and influence diverse stakeholders, including Product Engineering Leaders, Customers, Design Authorities, Project Management, IS/IT, research partners and academic collaborators. Highly effective in a matrix-based organisation; a collaborative team player who drives outcomes while maintaining scientific rigour. Excellent communication skills; able to explain complex AI research concepts clearly to technical and non-technical audiences. Curious, creative and intellectually rigorous, with the ability to challenge constructively and develop novel solutions to ambiguous problems. Encourages an open environment where ideas are shared, technical debate is welcomed and innovation thrives. Desirable PhD or equivalent research experience in Artificial Intelligence, Machine Learning, Computer Science, Mathematics, Engineering, Physics or a related discipline. Peer-reviewed publications, patents, invention disclosures, open-source contributions or recognised technical innovations. Experience with governance of architecture, research designs or detailed technical designs throughout the project lifecycle. Experience with large-scale data initiatives, data labelling strategies, synthetic data generation and data quality management. Familiarity with MLOps practices and cloud platforms for AI deployment. Experience working with academic partners, research institutions, grant-funded programmes or collaborative research consortia. Experience contributing to bids, proposals, customer demonstrations or externally funded innovation activities. Knowledge of cloud AI services, HPC environments, containerisation and secure research environments is desirable. Security Clearance statement Due the nature of the work that we do at Thales, many of our roles are subject to security restrictions. This role requires you to be a sole British National and achieve Security Clearance (SC) without any caveats. It would be advantageous if currently held, however, if not currently held, it is a requirement that the successful applicant undergo, achieve, and maintain SC Clearance prior to commencing employment. Please visit the UKSV website for further guidance- United Kingdom Security Vetting - GOV.UK ( ) To be eligible for full SC, you generally need to have resided in the UK for the last 5 years. In some circumstances . click apply for full job details
White Collar Factory (95009), United Kingdom, London, London Staff Software Engineer - Machine Learning About this role We're on a mission to transform the way we use data and AI to service our customers and drive efficiency across the business. Do you love shaping the technical landscape and driving innovation across the organisation? Are you passionate about solving complex ML and AI challenges and supporting multiple teams toward a shared technical vision? At Capital One, you'll be part of a community of technical leaders who drive engineering excellence, foster innovation, and deliver impactful ML/AI and Gen AI solutions that meet real customer needs. What You'll Do Own and drive the ML/AI technical strategy for UK use cases, spanning multiple teams and influencing the overall technical direction for AI adoption Lead and coordinate ML engineering efforts across multiple teams, ensuring alignment with broader business objectives, enterprise platform capabilities, and technology strategy Provide technical consultancy to teams delivering AI use cases, guiding architectural decisions, solution design, and effective use of enterprise ML/AI platforms and capabilities Proactively identify emerging ML/AI patterns, define and evangelise best practices, and establish reusable approaches that enhance delivery of AI use cases across the business Drive MLOps standards and practices across teams, including CI/CD for models, automated testing, monitoring, and deployment pipelines Collaborate with enterprise platform and data science teams, contributing to platform capabilities where appropriate and partnering on use case delivery Build and maintain strong relationships with key stakeholders, including senior leadership, product owners, data science teams, and enterprise platform partners Represent Capital One in external ML/AI technical forums, contributing to industry discussions Develop and advocate for strategies to proactively manage technical debt across ML/AI systems Actively mentor and develop engineers, fostering a culture of continuous learning What we're looking for Deep expertise in Python and ML engineering Deep expertise in ML/AI systems design, MLOps, and cloud-native architectures Track record of leading ML/AI technical initiatives across multiple teams Strong experience with cloud platforms (AWS, Azure, GCP) Experience with ML frameworks (PyTorch, TensorFlow, scikit-learn) and Gen AI/Agentic frameworks (LangGraph, LangChain, VectorDBs, RAG) Understanding of responsible AI practices, including guardrails, hallucination mitigation, and output quality management for AI systems Experience designing and scaling low-latency, customer-facing ML/AI architectures Proven experience setting a multi-team ML/AI technical vision and strategy Strong track record of technical leadership and influence without authority Experience driving ML engineering standards and best practices across organisations Deep understanding of the full ML/AI development lifecycle, including model serving, data pipelines, and Gen AI systems Experience leveraging enterprise platforms to deliver business use cases at scale Experience of steering Communities of Practice or technical forums Strong business acumen and ability to translate ML/AI concepts for various audiences Where and how you'll work This is a permanent position based in our London office. We have a hybrid working model which gives you flexibility to work from our office and from home. We're big on collaboration and connection, so you'll be based in our London office 3 days a week on Tuesdays, Wednesdays and Thursdays. What's in it for you Bring us all this - and you'll be well rewarded with a role contributing to the roadmap of an organisation committed to transformation We offer high performers strong and diverse career progression, investing heavily in developing great people through our Capital One University training programmes (and appropriate external providers) Immediate access to our core benefits including pension scheme, bonus, generous holiday entitlement and private medical insurance - with flexible benefits available including season-ticket loans, cycle to work scheme and enhanced parental leave Open-plan workspaces and accessible facilities designed to inspire and support you. Our Nottingham head-office has a fully-serviced gym, subsidised restaurant, mindfulness and music rooms. What you should know about how we recruit We pride ourselves on hiring the best people, not the same people. Building diverse and inclusive teams is the right thing to do and the smart thing to do. We want to work with top talent: whoever you are, whatever you look like, wherever you come from. We know it's about what you do, not just what you say. That's why we make our recruitment process fair and accessible. And we offer benefits that attract people at all ages and stages. We also partner with organisations including the Women in Finance and Race At Work Charters, Stonewall and upReach to find people from every walk of life and help them thrive with us. We have a whole host of internal networks and support groups you could be involved in, to name a few: REACH - Race Equality and Culture Heritage group focuses on representation, retention and engagement for associates from minority ethnic groups and allies OutFront - to provide LGBTQ+ support for all associates Mind Your Mind - signposting support and promoting positive mental wellbeing for all Women in Tech - promoting an inclusive environment in tech EmpowHER - network of female associates and allies focusing on developing future leaders, particularly for female talent in our industry Enabled - focused on supporting associates with disabilities and neurodiversity Capital One is committed to diversity in the workplace. If you require a reasonable adjustment, please contact All information will be kept confidential and will only be used for the purpose of applying a reasonable adjustment. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC). Who We Are At Capital One, we're building a leading information-based technology company. Still founder-led by Chairman and Chief Executive Officer Richard Fairbank, Capital One is on a mission to help our customers succeed by bringing ingenuity, simplicity, and humanity to banking. We measure our efforts by the success our customers enjoy and the advocacy they exhibit. We are succeeding because they are succeeding. Guided by our shared values, we thrive in an environment where collaboration and openness are valued. We believe that innovation is powered by perspective and that teamwork and respect for each other lead to superior results. We elevate each other and obsess about doing the right thing. Our associates serve with humility and a deep respect for their responsibility in helping our customers achieve their goals and realize their dreams. Together, we are on a quest to change banking for good.
Oct 21, 2026
Full time
White Collar Factory (95009), United Kingdom, London, London Staff Software Engineer - Machine Learning About this role We're on a mission to transform the way we use data and AI to service our customers and drive efficiency across the business. Do you love shaping the technical landscape and driving innovation across the organisation? Are you passionate about solving complex ML and AI challenges and supporting multiple teams toward a shared technical vision? At Capital One, you'll be part of a community of technical leaders who drive engineering excellence, foster innovation, and deliver impactful ML/AI and Gen AI solutions that meet real customer needs. What You'll Do Own and drive the ML/AI technical strategy for UK use cases, spanning multiple teams and influencing the overall technical direction for AI adoption Lead and coordinate ML engineering efforts across multiple teams, ensuring alignment with broader business objectives, enterprise platform capabilities, and technology strategy Provide technical consultancy to teams delivering AI use cases, guiding architectural decisions, solution design, and effective use of enterprise ML/AI platforms and capabilities Proactively identify emerging ML/AI patterns, define and evangelise best practices, and establish reusable approaches that enhance delivery of AI use cases across the business Drive MLOps standards and practices across teams, including CI/CD for models, automated testing, monitoring, and deployment pipelines Collaborate with enterprise platform and data science teams, contributing to platform capabilities where appropriate and partnering on use case delivery Build and maintain strong relationships with key stakeholders, including senior leadership, product owners, data science teams, and enterprise platform partners Represent Capital One in external ML/AI technical forums, contributing to industry discussions Develop and advocate for strategies to proactively manage technical debt across ML/AI systems Actively mentor and develop engineers, fostering a culture of continuous learning What we're looking for Deep expertise in Python and ML engineering Deep expertise in ML/AI systems design, MLOps, and cloud-native architectures Track record of leading ML/AI technical initiatives across multiple teams Strong experience with cloud platforms (AWS, Azure, GCP) Experience with ML frameworks (PyTorch, TensorFlow, scikit-learn) and Gen AI/Agentic frameworks (LangGraph, LangChain, VectorDBs, RAG) Understanding of responsible AI practices, including guardrails, hallucination mitigation, and output quality management for AI systems Experience designing and scaling low-latency, customer-facing ML/AI architectures Proven experience setting a multi-team ML/AI technical vision and strategy Strong track record of technical leadership and influence without authority Experience driving ML engineering standards and best practices across organisations Deep understanding of the full ML/AI development lifecycle, including model serving, data pipelines, and Gen AI systems Experience leveraging enterprise platforms to deliver business use cases at scale Experience of steering Communities of Practice or technical forums Strong business acumen and ability to translate ML/AI concepts for various audiences Where and how you'll work This is a permanent position based in our London office. We have a hybrid working model which gives you flexibility to work from our office and from home. We're big on collaboration and connection, so you'll be based in our London office 3 days a week on Tuesdays, Wednesdays and Thursdays. What's in it for you Bring us all this - and you'll be well rewarded with a role contributing to the roadmap of an organisation committed to transformation We offer high performers strong and diverse career progression, investing heavily in developing great people through our Capital One University training programmes (and appropriate external providers) Immediate access to our core benefits including pension scheme, bonus, generous holiday entitlement and private medical insurance - with flexible benefits available including season-ticket loans, cycle to work scheme and enhanced parental leave Open-plan workspaces and accessible facilities designed to inspire and support you. Our Nottingham head-office has a fully-serviced gym, subsidised restaurant, mindfulness and music rooms. What you should know about how we recruit We pride ourselves on hiring the best people, not the same people. Building diverse and inclusive teams is the right thing to do and the smart thing to do. We want to work with top talent: whoever you are, whatever you look like, wherever you come from. We know it's about what you do, not just what you say. That's why we make our recruitment process fair and accessible. And we offer benefits that attract people at all ages and stages. We also partner with organisations including the Women in Finance and Race At Work Charters, Stonewall and upReach to find people from every walk of life and help them thrive with us. We have a whole host of internal networks and support groups you could be involved in, to name a few: REACH - Race Equality and Culture Heritage group focuses on representation, retention and engagement for associates from minority ethnic groups and allies OutFront - to provide LGBTQ+ support for all associates Mind Your Mind - signposting support and promoting positive mental wellbeing for all Women in Tech - promoting an inclusive environment in tech EmpowHER - network of female associates and allies focusing on developing future leaders, particularly for female talent in our industry Enabled - focused on supporting associates with disabilities and neurodiversity Capital One is committed to diversity in the workplace. If you require a reasonable adjustment, please contact All information will be kept confidential and will only be used for the purpose of applying a reasonable adjustment. For technical support or questions about Capital One's recruiting process, please send an email to Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site. Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC). Who We Are At Capital One, we're building a leading information-based technology company. Still founder-led by Chairman and Chief Executive Officer Richard Fairbank, Capital One is on a mission to help our customers succeed by bringing ingenuity, simplicity, and humanity to banking. We measure our efforts by the success our customers enjoy and the advocacy they exhibit. We are succeeding because they are succeeding. Guided by our shared values, we thrive in an environment where collaboration and openness are valued. We believe that innovation is powered by perspective and that teamwork and respect for each other lead to superior results. We elevate each other and obsess about doing the right thing. Our associates serve with humility and a deep respect for their responsibility in helping our customers achieve their goals and realize their dreams. Together, we are on a quest to change banking for good.
Sanderson are working with a consulting client who are looking to grow their Data capability. The client is seeking candidates who have experience Data Engineering and cloud platforms. Key skills and responsibilities: Strong proficiency in Python Extensive experience with cloud platforms Experience with: Data warehousing and lake architectures ETL/ELT pipeline development SQL and NoSQL databases Distributed computing frameworks Software development best practices Containerisation tools Experience with Infrastructure as Code tools Strong understanding of data modelling and system architecture Knowledge of common machine learning frameworks and models A good understanding of approaches to monitoring ML models in production This role will require you to be willing and eligible to undergo UK security clearance. If you're interested in the above, apply or reach out to
Oct 20, 2026
Full time
Sanderson are working with a consulting client who are looking to grow their Data capability. The client is seeking candidates who have experience Data Engineering and cloud platforms. Key skills and responsibilities: Strong proficiency in Python Extensive experience with cloud platforms Experience with: Data warehousing and lake architectures ETL/ELT pipeline development SQL and NoSQL databases Distributed computing frameworks Software development best practices Containerisation tools Experience with Infrastructure as Code tools Strong understanding of data modelling and system architecture Knowledge of common machine learning frameworks and models A good understanding of approaches to monitoring ML models in production This role will require you to be willing and eligible to undergo UK security clearance. If you're interested in the above, apply or reach out to
AI Product Engineer - AI/Hardware/Manufacturing Location: Central London, primarily office-based with some flexibility. We're partnering with an AI startup building software to help engineers design and develop physical products faster. Combining machine learning with complex engineering software, their platform helps bring new hardware ideas closer to production. They're looking for an AI Product Engineer to build the interface between users and their AI-powered design systems. This is a hands-on opportunity to work across frontend, backend, and applied AI, helping engineers turn ideas into structured workflows and inspect and refine the results. What you'll be doing Build polished applications that help engineers describe, generate, and refine designs. Translate natural-language requests, images, and drawings into structured engineering specifications. Design agentic systems that interact reliably with tools, backend services, and CAD and geometry systems. Evaluate models, investigate failures, and decide when adaptation or fine-tuning is needed. Create workflows that let users review, correct, and guide AI-generated outputs. Own features across frontend, backend, and applied AI, from initial design through implementation. What we're looking for Strong product-engineering fundamentals and experience delivering user-facing software. A deep understanding of LLM behaviour , beyond prompting and basic API integration. Experience building agents that use tools and interact with backend services. Sound judgement around model selection, evaluation, and reliability. Confidence translating ambiguous user needs into practical product features. The ability to work across frontend, backend, and applied ML within a small, highly technical team. Experience that would stand out React, TypeScript, Python , and modern application architecture. Structured generation, tool use, RAG , model adaptation, or fine-tuning. Multimodal systems involving text, images, drawings, or technical inputs. Evaluation frameworks, observability, and testing for AI systems. CAD, geometry, engineering software, or human-in-the-loop workflows. We're interested in engineers who combine strong coding skills, a practical understanding of AI, and thoughtful product decisions to build software that works reliably for users.
Oct 20, 2026
Full time
AI Product Engineer - AI/Hardware/Manufacturing Location: Central London, primarily office-based with some flexibility. We're partnering with an AI startup building software to help engineers design and develop physical products faster. Combining machine learning with complex engineering software, their platform helps bring new hardware ideas closer to production. They're looking for an AI Product Engineer to build the interface between users and their AI-powered design systems. This is a hands-on opportunity to work across frontend, backend, and applied AI, helping engineers turn ideas into structured workflows and inspect and refine the results. What you'll be doing Build polished applications that help engineers describe, generate, and refine designs. Translate natural-language requests, images, and drawings into structured engineering specifications. Design agentic systems that interact reliably with tools, backend services, and CAD and geometry systems. Evaluate models, investigate failures, and decide when adaptation or fine-tuning is needed. Create workflows that let users review, correct, and guide AI-generated outputs. Own features across frontend, backend, and applied AI, from initial design through implementation. What we're looking for Strong product-engineering fundamentals and experience delivering user-facing software. A deep understanding of LLM behaviour , beyond prompting and basic API integration. Experience building agents that use tools and interact with backend services. Sound judgement around model selection, evaluation, and reliability. Confidence translating ambiguous user needs into practical product features. The ability to work across frontend, backend, and applied ML within a small, highly technical team. Experience that would stand out React, TypeScript, Python , and modern application architecture. Structured generation, tool use, RAG , model adaptation, or fine-tuning. Multimodal systems involving text, images, drawings, or technical inputs. Evaluation frameworks, observability, and testing for AI systems. CAD, geometry, engineering software, or human-in-the-loop workflows. We're interested in engineers who combine strong coding skills, a practical understanding of AI, and thoughtful product decisions to build software that works reliably for users.
Role: Senior Cyber Exposure & Vulnerability Manager Location: Corporate Offices / Hybrid (UK) Industry: Financial Services / Insurance (Regulated Environment) Type: Full-Time, Permanent Senior Cyber Exposure & Vulnerability Manager Hands-On AI & Exposure Leader End-to-end operational ownership of enterprise exposure, vulnerability management, and zero-day response capabilities. Drive modern risk-based prioritisation and AI-driven automation across cloud, infrastructure, and application estates. Key focus: Strategy execution, cross-CIO collaboration, backlog reduction, and executive-level governance. About the Opportunity A leading UK financial services organisation is looking for a high-performing Senior Cyber Exposure & Vulnerability Manager to own and evolve its end-to-end vulnerability management and response framework. Reporting directly to the Deputy CISO, you will act as the organizational authority on exposure management. In this hands-on, high-impact role, you will bridge the gap between technical risk and business reality-ensuring vulnerabilities across infrastructure, cloud, and applications are identified, prioritised, remediated, and reported in a disciplined, risk-based manner. Additionally, you will champion the practical application of AI and intelligent automation to modernise triage, threat correlation, and remediation workflows. Key Accountabilities End-to-End Vulnerability Ownership: Own the enterprise lifecycle across infrastructure, cloud, apps, and third-party services-covering scanning, triage, risk prioritisation, mitigation, and verification. Hands-On Delivery & Response: Manage vulnerability backlogs, ageing, high/critical remediation activity, scan coverage, and emergency response to zero-day exposures. AI, Automation & Innovation: Champion the practical use of AI and data-driven insights to optimise triage, reduce false positives, perform root-cause clustering, and automate reporting. Cross-CIO Collaboration: Partner with Engineering, Cloud, Data, and Architecture teams to embed vulnerability response into existing delivery pipelines rather than treating it as a parallel task. Governance & Executive Reporting: Define and track KPIs/KRIs (SLAs, exposure trends, backlog health) and deliver concise, actionable reporting for CIO leadership, Audit, and CISO/Board forums. Risk & Regulatory Support: Align exposure decisions to organizational risk appetite, manage formal risk acceptances, and drive audit and regulatory remediation actions to closure. Required Skills & Experience Enterprise Exposure Experience: Proven track record running vulnerability management and response within complex, highly regulated environments (Financial Services/Insurance preferred). Technical Breadth: Strong hands-on understanding of vulnerability management principles, tooling, and remediation across cloud, hybrid infrastructure, applications, and platforms. Risk-Based Prioritisation: Expertise in context-aware risk scoring (combining CVSS, threat intelligence, asset criticality, attack surface, and business impact). Forward-Looking Mindset: Genuine interest and practical experience in leveraging AI, machine learning, or automated tooling to streamline cyber operations. Influence & Stakeholder Management: Ability to translate complex technical vulnerabilities into clear business risk and drive remediation across engineering teams without relying on formal authority. To Apply If you are an energetic, delivery-focused vulnerability leader looking to drive modern, AI-enabled exposure management within a fast-paced environment, please submit your CV for immediate consideration.
Oct 20, 2026
Full time
Role: Senior Cyber Exposure & Vulnerability Manager Location: Corporate Offices / Hybrid (UK) Industry: Financial Services / Insurance (Regulated Environment) Type: Full-Time, Permanent Senior Cyber Exposure & Vulnerability Manager Hands-On AI & Exposure Leader End-to-end operational ownership of enterprise exposure, vulnerability management, and zero-day response capabilities. Drive modern risk-based prioritisation and AI-driven automation across cloud, infrastructure, and application estates. Key focus: Strategy execution, cross-CIO collaboration, backlog reduction, and executive-level governance. About the Opportunity A leading UK financial services organisation is looking for a high-performing Senior Cyber Exposure & Vulnerability Manager to own and evolve its end-to-end vulnerability management and response framework. Reporting directly to the Deputy CISO, you will act as the organizational authority on exposure management. In this hands-on, high-impact role, you will bridge the gap between technical risk and business reality-ensuring vulnerabilities across infrastructure, cloud, and applications are identified, prioritised, remediated, and reported in a disciplined, risk-based manner. Additionally, you will champion the practical application of AI and intelligent automation to modernise triage, threat correlation, and remediation workflows. Key Accountabilities End-to-End Vulnerability Ownership: Own the enterprise lifecycle across infrastructure, cloud, apps, and third-party services-covering scanning, triage, risk prioritisation, mitigation, and verification. Hands-On Delivery & Response: Manage vulnerability backlogs, ageing, high/critical remediation activity, scan coverage, and emergency response to zero-day exposures. AI, Automation & Innovation: Champion the practical use of AI and data-driven insights to optimise triage, reduce false positives, perform root-cause clustering, and automate reporting. Cross-CIO Collaboration: Partner with Engineering, Cloud, Data, and Architecture teams to embed vulnerability response into existing delivery pipelines rather than treating it as a parallel task. Governance & Executive Reporting: Define and track KPIs/KRIs (SLAs, exposure trends, backlog health) and deliver concise, actionable reporting for CIO leadership, Audit, and CISO/Board forums. Risk & Regulatory Support: Align exposure decisions to organizational risk appetite, manage formal risk acceptances, and drive audit and regulatory remediation actions to closure. Required Skills & Experience Enterprise Exposure Experience: Proven track record running vulnerability management and response within complex, highly regulated environments (Financial Services/Insurance preferred). Technical Breadth: Strong hands-on understanding of vulnerability management principles, tooling, and remediation across cloud, hybrid infrastructure, applications, and platforms. Risk-Based Prioritisation: Expertise in context-aware risk scoring (combining CVSS, threat intelligence, asset criticality, attack surface, and business impact). Forward-Looking Mindset: Genuine interest and practical experience in leveraging AI, machine learning, or automated tooling to streamline cyber operations. Influence & Stakeholder Management: Ability to translate complex technical vulnerabilities into clear business risk and drive remediation across engineering teams without relying on formal authority. To Apply If you are an energetic, delivery-focused vulnerability leader looking to drive modern, AI-enabled exposure management within a fast-paced environment, please submit your CV for immediate consideration.
West London location - 2 days on site p/week Active SC required Up to £700/d inside ir35 3-year engagement Experience required in Model Development, Data Pipelines, Production Deployment Role Opportunity This is a long-term engagement with a leading Consultancy supplying into the Public Sector for an experienced Machine Learning Engineer with SC Clearance. Key Responsibilities: Develop and optimise ML models for personalisation and recommendations Build scalable data pipelines and feature engineering workflows Deploy, monitor and optimise ML models in production Lead A/B testing and experimentation to improve model performance Collaborate with cross-functional teams to deliver ML solutions Evaluate and apply emerging ML and deep learning techniques Key Skills Required: Machine Learning / Deep Learning Recommendation & Personalisation Systems Data Pipelines & Feature Engineering MLOps & Production Deployment A/B Testing & Experimentation Python / ML Frameworks Large-scale Structured & Unstructured Data To be Considered: Please either apply by clicking online or emailing me directly to . For further information please call me on or . If unavailable, please leave a message and either myself or one of my colleagues will respond. By applying for this role, you give express consent for us to process & submit (subject to required skills) your application to our client in conjunction with this vacancy only. Also feel free to follow me on or connect with me on LinkedIn, just search Henry Clay-Davies. I look forward to hearing from you!
Oct 19, 2026
Full time
West London location - 2 days on site p/week Active SC required Up to £700/d inside ir35 3-year engagement Experience required in Model Development, Data Pipelines, Production Deployment Role Opportunity This is a long-term engagement with a leading Consultancy supplying into the Public Sector for an experienced Machine Learning Engineer with SC Clearance. Key Responsibilities: Develop and optimise ML models for personalisation and recommendations Build scalable data pipelines and feature engineering workflows Deploy, monitor and optimise ML models in production Lead A/B testing and experimentation to improve model performance Collaborate with cross-functional teams to deliver ML solutions Evaluate and apply emerging ML and deep learning techniques Key Skills Required: Machine Learning / Deep Learning Recommendation & Personalisation Systems Data Pipelines & Feature Engineering MLOps & Production Deployment A/B Testing & Experimentation Python / ML Frameworks Large-scale Structured & Unstructured Data To be Considered: Please either apply by clicking online or emailing me directly to . For further information please call me on or . If unavailable, please leave a message and either myself or one of my colleagues will respond. By applying for this role, you give express consent for us to process & submit (subject to required skills) your application to our client in conjunction with this vacancy only. Also feel free to follow me on or connect with me on LinkedIn, just search Henry Clay-Davies. I look forward to hearing from you!
Trainee AI Engineer - No Experience Needed Future-proof your career in Artificial Intelligence - starting today. Looking for a career change? Currently employed but want something better? Or maybe you're between jobs and ready for a fresh start? ITOL Recruit's AI Traineeship is designed to get you into one of the fastest-growing industries with zero experience required. Train online at your own pace and land your first AI Engineer role in 1-3 months. Please note this is a training course and fees apply Job guaranteed - complete the programme and get a job or get your money back. Our candidates earn £28,000-£45,000. Why AI? AI is reshaping every industry you can think of. Healthcare, finance, retail, and manufacturing - they're all scrambling for skilled professionals. The demand far outstrips supply, which means excellent salaries, flexible working arrangements, and genuine job security. How It Works Step 1 - AI Engineering Fundamentals Start with the basics of AI, including neural networks and large language models, to build a solid foundation in AI engineering. Step 2 - Data Fundamentals Understand the data workflow, from collection to cleaning, and learn how to prepare data for AI applications. Step 3 - Notebooks & IDEs Get hands-on with industry-standard tools like Jupyter Notebooks and VS Code to develop AI systems. Step 4 - Python Programming Master Python, covering everything from the basics to object-oriented programming (OOP). Step 5 - Python Streamlit Project Apply your Python skills by building a car price prediction app using Python and Streamlit. Step 6 - Python for Data Learn essential Python libraries like NumPy, Pandas, and Matplotlib for data manipulation and visualisation. Step 7 - AI Sentiment Analysis Project Work with Hugging Face to build a sentiment analysis classifier using real-world AI techniques. Step 8 - AI Prompt Engineering Master prompt engineering, learning how to craft effective prompts for controlling AI outputs. Step 9 - Retrieval-Augmented Generation (RAG) Learn how to integrate external knowledge into AI systems using RAG techniques and vector databases. Step 10 - AI Specialised Customer Service Chatbot Project Combine prompt engineering and RAG to build an AI-powered customer service chatbot, delivering intelligent responses using vector databases and knowledge bases. Step 11 - Machine Learning Fundamentals Understand machine learning principles and algorithms, and how to train and test models using scikit-learn. Step 12 - Machine Learning Project Put your machine learning knowledge into practice with a hands-on project. Step 13 - AI & Data Ethics Study the ethical considerations in AI, including issues of bias, fairness, and data privacy. Step 14 - Oral Exam Complete a virtual oral exam to assess your understanding and ability to apply your learning. Step 15 - AWS Certified Cloud Practitioner Finish with the AWS Certified Cloud Practitioner course and exam to gain essential cloud computing knowledge. What You Get 100% online, self-paced training Microsoft AI-900 certification included 1-to-1 tutor and recruitment support Real-world project experience Job guarantee - get a job or your money back Starting salary of £28,000-£45,000 We Get You Hired We're not new to this. ITOL Recruit has 15+ years of experience and has placed over 5,000 people into new roles. Our job programmes include certified tutors, UK-accredited qualifications, and one-on-one support from a recruitment adviser focused on placing you. We don't believe in empty promises. Complete our programme, follow the process, and if you don't land a job, you get your money back. "Five months from complete beginner to AI engineer. Best decision I ever made." - Jamie W., now working as a Junior AI Engineer in London Ready to Start? If you're motivated, curious, and excited about technology, we'll help you turn that into a career you can be proud of. Apply now, and one of our expert Career Advisors will be in touch within 4 working hours to guide you through your next steps.
Oct 18, 2026
Full time
Trainee AI Engineer - No Experience Needed Future-proof your career in Artificial Intelligence - starting today. Looking for a career change? Currently employed but want something better? Or maybe you're between jobs and ready for a fresh start? ITOL Recruit's AI Traineeship is designed to get you into one of the fastest-growing industries with zero experience required. Train online at your own pace and land your first AI Engineer role in 1-3 months. Please note this is a training course and fees apply Job guaranteed - complete the programme and get a job or get your money back. Our candidates earn £28,000-£45,000. Why AI? AI is reshaping every industry you can think of. Healthcare, finance, retail, and manufacturing - they're all scrambling for skilled professionals. The demand far outstrips supply, which means excellent salaries, flexible working arrangements, and genuine job security. How It Works Step 1 - AI Engineering Fundamentals Start with the basics of AI, including neural networks and large language models, to build a solid foundation in AI engineering. Step 2 - Data Fundamentals Understand the data workflow, from collection to cleaning, and learn how to prepare data for AI applications. Step 3 - Notebooks & IDEs Get hands-on with industry-standard tools like Jupyter Notebooks and VS Code to develop AI systems. Step 4 - Python Programming Master Python, covering everything from the basics to object-oriented programming (OOP). Step 5 - Python Streamlit Project Apply your Python skills by building a car price prediction app using Python and Streamlit. Step 6 - Python for Data Learn essential Python libraries like NumPy, Pandas, and Matplotlib for data manipulation and visualisation. Step 7 - AI Sentiment Analysis Project Work with Hugging Face to build a sentiment analysis classifier using real-world AI techniques. Step 8 - AI Prompt Engineering Master prompt engineering, learning how to craft effective prompts for controlling AI outputs. Step 9 - Retrieval-Augmented Generation (RAG) Learn how to integrate external knowledge into AI systems using RAG techniques and vector databases. Step 10 - AI Specialised Customer Service Chatbot Project Combine prompt engineering and RAG to build an AI-powered customer service chatbot, delivering intelligent responses using vector databases and knowledge bases. Step 11 - Machine Learning Fundamentals Understand machine learning principles and algorithms, and how to train and test models using scikit-learn. Step 12 - Machine Learning Project Put your machine learning knowledge into practice with a hands-on project. Step 13 - AI & Data Ethics Study the ethical considerations in AI, including issues of bias, fairness, and data privacy. Step 14 - Oral Exam Complete a virtual oral exam to assess your understanding and ability to apply your learning. Step 15 - AWS Certified Cloud Practitioner Finish with the AWS Certified Cloud Practitioner course and exam to gain essential cloud computing knowledge. What You Get 100% online, self-paced training Microsoft AI-900 certification included 1-to-1 tutor and recruitment support Real-world project experience Job guarantee - get a job or your money back Starting salary of £28,000-£45,000 We Get You Hired We're not new to this. ITOL Recruit has 15+ years of experience and has placed over 5,000 people into new roles. Our job programmes include certified tutors, UK-accredited qualifications, and one-on-one support from a recruitment adviser focused on placing you. We don't believe in empty promises. Complete our programme, follow the process, and if you don't land a job, you get your money back. "Five months from complete beginner to AI engineer. Best decision I ever made." - Jamie W., now working as a Junior AI Engineer in London Ready to Start? If you're motivated, curious, and excited about technology, we'll help you turn that into a career you can be proud of. Apply now, and one of our expert Career Advisors will be in touch within 4 working hours to guide you through your next steps.
Our client is in the Financial Sector and is looking to grow their team with a new AI Engineer. The role is hybrid with 2 days in Central London, 3 days at home. This is a brand new role in the AI team of 20 to work on new projects and products, using data to make smarter, better decisions. Client Details Our client is in the Financial Sector and is looking to grow their team with a new AI Engineer. The role is hybrid with 2 days in Central London, 3 days at home. This is a brand new role in the AI team of 20 to work on new projects and products, using data to make smarter, better decisions. Description Design, develop, and implement AI-driven solutions to address complex business challenges. Collaborate with cross-functional teams to integrate AI technologies into existing systems. Research and apply advanced machine learning algorithms and techniques to improve business processes. Analyse large datasets to derive actionable insights and drive data-driven decision-making. Develop and maintain scalable AI models using industry best practices. Monitor the performance of AI systems and troubleshoot issues as they arise. Provide technical expertise and guidance to colleagues and stakeholders. Stay up-to-date with emerging trends and advancements in AI and machine learning. Profile Must haves: Software Engineering experience - ideally C# or Python Azure (Azure Fabric, Data Factory, ML Studio, Foundry, Synapse, Cosmos etc) Experience dealing with stakeholders, working with a wider tech team, collabortation etc Experience designing, testing and deploying production-scale GenAI (not just proof of concepts) Then a mixture of the following on top: GenAI LLM APIs Experience designing, testing and deploying AI/ML solutions Chat Bots / Agents FastAPI Microsoft Agent Framework LangChain Vector database ML Engineering Job Offer Car allowance of 5k Private medical 25 days + BHS Option to buy 10 more holidays Matched pension Life assurance
Oct 16, 2026
Full time
Our client is in the Financial Sector and is looking to grow their team with a new AI Engineer. The role is hybrid with 2 days in Central London, 3 days at home. This is a brand new role in the AI team of 20 to work on new projects and products, using data to make smarter, better decisions. Client Details Our client is in the Financial Sector and is looking to grow their team with a new AI Engineer. The role is hybrid with 2 days in Central London, 3 days at home. This is a brand new role in the AI team of 20 to work on new projects and products, using data to make smarter, better decisions. Description Design, develop, and implement AI-driven solutions to address complex business challenges. Collaborate with cross-functional teams to integrate AI technologies into existing systems. Research and apply advanced machine learning algorithms and techniques to improve business processes. Analyse large datasets to derive actionable insights and drive data-driven decision-making. Develop and maintain scalable AI models using industry best practices. Monitor the performance of AI systems and troubleshoot issues as they arise. Provide technical expertise and guidance to colleagues and stakeholders. Stay up-to-date with emerging trends and advancements in AI and machine learning. Profile Must haves: Software Engineering experience - ideally C# or Python Azure (Azure Fabric, Data Factory, ML Studio, Foundry, Synapse, Cosmos etc) Experience dealing with stakeholders, working with a wider tech team, collabortation etc Experience designing, testing and deploying production-scale GenAI (not just proof of concepts) Then a mixture of the following on top: GenAI LLM APIs Experience designing, testing and deploying AI/ML solutions Chat Bots / Agents FastAPI Microsoft Agent Framework LangChain Vector database ML Engineering Job Offer Car allowance of 5k Private medical 25 days + BHS Option to buy 10 more holidays Matched pension Life assurance
Lead Databricks Architect - London (Hybrid) Databricks - Azure - Data & AI Leadership - Up to £115,000 Are you looking to take ownership of large-scale Data & AI transformation programmes while leading teams and shaping technical delivery? Due to continued growth, we're hiring multiple Lead Databricks Architects to join a rapidly expanding Data & AI practice delivering complex transformation programmes for enterprise organisations across a range of industries. This is a leadership-focused role combining architecture, technical leadership and delivery oversight. You'll work closely with architects, delivery leads and senior stakeholders to define solution strategy, oversee engineering delivery and build modern Databricks-based platforms that enable advanced analytics, machine learning and AI initiatives. You'll join a high-performing team of Data Engineers, Architects and AI specialists, working on enterprise-scale programmes that utilise the latest technologies across Databricks, Azure and modern Data & AI ecosystems. If you enjoy leading technical teams, influencing architecture decisions and helping organisations unlock the value of their data, this is an excellent opportunity to make a significant impact. You Will Work With Defining architecture and technical strategy for enterprise-scale Databricks programmes Leading and mentoring teams of Data Engineers and technical specialists Designing modern Lakehouse architectures using Databricks and Azure Collaborating with stakeholders to shape solution roadmaps and delivery plans Overseeing engineering delivery, quality standards and technical governance Driving best practice across data engineering, analytics and AI initiatives Supporting machine learning, GenAI and emerging AI workloads Conducting discovery workshops and architecture reviews Managing technical risks, dependencies and architectural decisions Supporting business growth through technical leadership and solution design Benefits Annual performance bonus Access to enterprise-scale Data & AI transformation programmes Industry-recognised training and certifications Clear progression into senior leadership positions Exposure to cutting-edge Databricks, AI and cloud technologies Private healthcare Pension scheme Flexible benefits package Collaborative and inclusive working environment Key Experience We're interested in speaking with experienced technical leaders who can combine strong Databricks expertise with architecture and delivery experience. Essential Strong hands-on Databricks experience Lakehouse Architecture Delta Lake & Unity Catalog Team leadership experience Azure/AWS/GCP Stakeholder management Enterprise-scale data platform delivery Desirable Databricks certifications MLflow Mosaic AI Vector Search Terraform Consultancy background Regulated industry experience Apply Now This is a great opportunity to join a growing Data & AI practice investing heavily in Databricks, AI and cloud technologies. With multiple positions available and significant investment in Data & AI capabilities, we're actively interviewing experienced architects and technical leaders. Whether you're currently a Databricks Architect, Lead Data Engineer, Principal Data Engineer, Data Platform Architect or Technical Lead, Apply now.
Oct 16, 2026
Full time
Lead Databricks Architect - London (Hybrid) Databricks - Azure - Data & AI Leadership - Up to £115,000 Are you looking to take ownership of large-scale Data & AI transformation programmes while leading teams and shaping technical delivery? Due to continued growth, we're hiring multiple Lead Databricks Architects to join a rapidly expanding Data & AI practice delivering complex transformation programmes for enterprise organisations across a range of industries. This is a leadership-focused role combining architecture, technical leadership and delivery oversight. You'll work closely with architects, delivery leads and senior stakeholders to define solution strategy, oversee engineering delivery and build modern Databricks-based platforms that enable advanced analytics, machine learning and AI initiatives. You'll join a high-performing team of Data Engineers, Architects and AI specialists, working on enterprise-scale programmes that utilise the latest technologies across Databricks, Azure and modern Data & AI ecosystems. If you enjoy leading technical teams, influencing architecture decisions and helping organisations unlock the value of their data, this is an excellent opportunity to make a significant impact. You Will Work With Defining architecture and technical strategy for enterprise-scale Databricks programmes Leading and mentoring teams of Data Engineers and technical specialists Designing modern Lakehouse architectures using Databricks and Azure Collaborating with stakeholders to shape solution roadmaps and delivery plans Overseeing engineering delivery, quality standards and technical governance Driving best practice across data engineering, analytics and AI initiatives Supporting machine learning, GenAI and emerging AI workloads Conducting discovery workshops and architecture reviews Managing technical risks, dependencies and architectural decisions Supporting business growth through technical leadership and solution design Benefits Annual performance bonus Access to enterprise-scale Data & AI transformation programmes Industry-recognised training and certifications Clear progression into senior leadership positions Exposure to cutting-edge Databricks, AI and cloud technologies Private healthcare Pension scheme Flexible benefits package Collaborative and inclusive working environment Key Experience We're interested in speaking with experienced technical leaders who can combine strong Databricks expertise with architecture and delivery experience. Essential Strong hands-on Databricks experience Lakehouse Architecture Delta Lake & Unity Catalog Team leadership experience Azure/AWS/GCP Stakeholder management Enterprise-scale data platform delivery Desirable Databricks certifications MLflow Mosaic AI Vector Search Terraform Consultancy background Regulated industry experience Apply Now This is a great opportunity to join a growing Data & AI practice investing heavily in Databricks, AI and cloud technologies. With multiple positions available and significant investment in Data & AI capabilities, we're actively interviewing experienced architects and technical leaders. Whether you're currently a Databricks Architect, Lead Data Engineer, Principal Data Engineer, Data Platform Architect or Technical Lead, Apply now.
AI Engineer / Machine Learning Engineer Hybrid (London) - Python - AWS - Databricks - Up to £100,000 We're partnered with an innovative, technology-led organisation that is investing heavily in AI and machine learning as a core part of its future growth. They're looking for an AI Engineer / Machine Learning Engineer to join a small, highly capable team where you'll have the autonomy, ownership and influence that's often missing in larger businesses. This isn't a research-focused role. It's about applying AI and machine learning to real business challenges, building production-ready solutions and owning projects from initial concept through to deployment and iteration. You'll be joining a close-knit engineering environment where your ideas will be heard, technical decisions won't get lost in layers of management and you'll have the opportunity to make a meaningful impact across the business. If you enjoy solving complex problems, working with modern technologies and taking ownership of what you build, this could be the role for you. You Will Work With Designing, building and deploying AI/ML solutions into production environments. Developing scalable backend applications, APIs and services using Python. Building cloud-native solutions within AWS environments. Creating and maintaining data pipelines and machine learning workflows. Monitoring, testing and optimising AI systems in production. Collaborating closely with engineering, product and data teams. Working across the full development lifecycle from design through to deployment and support. Benefits Join a small team where your contributions have a direct impact End-to-end ownership from design through to production Opportunity to shape the future AI capability of the business Work across the full AI/ML lifecycle rather than specialising in one area Work alongside experienced engineers in a highly collaborative environment Clear progression opportunities as the function continues to grow Flexible working environment focused on outcomes rather than micromanagement Key Experience Strong commercial experience in either Machine Learning / Data Science or Backend Engineering Demonstrable overlap between software engineering and machine learning Excellent Python development skills. Experience deploying solutions into production rather than purely building models or conducting research Exposure to cloud platforms, ideally AWS. Docker and containerisation experience Knowledge of Databricks, MLOps or modern AI tooling would be beneficial Strong engineering fundamentals and a passion for building high-quality solutions. Comfortable working in an environment with high responsibility and high expectations. Apply Now Opportunities offering this level of ownership, technical challenge and autonomy don't come along often. If you're looking for a role where you can influence the product, technology and future direction of a growing business.
Oct 16, 2026
Full time
AI Engineer / Machine Learning Engineer Hybrid (London) - Python - AWS - Databricks - Up to £100,000 We're partnered with an innovative, technology-led organisation that is investing heavily in AI and machine learning as a core part of its future growth. They're looking for an AI Engineer / Machine Learning Engineer to join a small, highly capable team where you'll have the autonomy, ownership and influence that's often missing in larger businesses. This isn't a research-focused role. It's about applying AI and machine learning to real business challenges, building production-ready solutions and owning projects from initial concept through to deployment and iteration. You'll be joining a close-knit engineering environment where your ideas will be heard, technical decisions won't get lost in layers of management and you'll have the opportunity to make a meaningful impact across the business. If you enjoy solving complex problems, working with modern technologies and taking ownership of what you build, this could be the role for you. You Will Work With Designing, building and deploying AI/ML solutions into production environments. Developing scalable backend applications, APIs and services using Python. Building cloud-native solutions within AWS environments. Creating and maintaining data pipelines and machine learning workflows. Monitoring, testing and optimising AI systems in production. Collaborating closely with engineering, product and data teams. Working across the full development lifecycle from design through to deployment and support. Benefits Join a small team where your contributions have a direct impact End-to-end ownership from design through to production Opportunity to shape the future AI capability of the business Work across the full AI/ML lifecycle rather than specialising in one area Work alongside experienced engineers in a highly collaborative environment Clear progression opportunities as the function continues to grow Flexible working environment focused on outcomes rather than micromanagement Key Experience Strong commercial experience in either Machine Learning / Data Science or Backend Engineering Demonstrable overlap between software engineering and machine learning Excellent Python development skills. Experience deploying solutions into production rather than purely building models or conducting research Exposure to cloud platforms, ideally AWS. Docker and containerisation experience Knowledge of Databricks, MLOps or modern AI tooling would be beneficial Strong engineering fundamentals and a passion for building high-quality solutions. Comfortable working in an environment with high responsibility and high expectations. Apply Now Opportunities offering this level of ownership, technical challenge and autonomy don't come along often. If you're looking for a role where you can influence the product, technology and future direction of a growing business.
