A leading financial innovation lab in London is seeking a Data & AI Scientist to develop production-grade AI solutions. The role involves architecting AgenticAI frameworks and scaling generative AI applications. Candidates should have a minimum of 2 years of experience in LLM applications and a strong background in Python and AI Engineering. This position offers a long-term contract with a hybrid work model, allowing flexibility and collaboration in a cutting-edge environment.
Mar 20, 2026
Full time
A leading financial innovation lab in London is seeking a Data & AI Scientist to develop production-grade AI solutions. The role involves architecting AgenticAI frameworks and scaling generative AI applications. Candidates should have a minimum of 2 years of experience in LLM applications and a strong background in Python and AI Engineering. This position offers a long-term contract with a hybrid work model, allowing flexibility and collaboration in a cutting-edge environment.
Overview - Featured Role Apply direct with Data Freelance Hub This role is for a Data & AI Scientist with a long term contract in London, offering a pay rate of "unknown." Key skills include advanced Python, AgenticAI tools, and experience with LLM applications. Hybrid work model; financial industry experience preferred. We are working with a leading edge financial innovation lab shaping the future of conversational banking. As a Data & AI Scientist, you will be at the forefront of the generative revolution, building production grade agentic workflows that redefine how customers interact with global banking systems. You will leverage advanced Python engineering and multi cloud infrastructure (Azure & GCP) to transition experimental AI into high impact, autonomous customer solutions. Responsibilities Architect and deploy production ready AgenticAI solutions using Langgraph, CrewAI, and multi agent frameworks. Design and scale RAG pipelines and generative search experiences, evolving standard vector search into fully conversational interfaces. Build robust integration patterns that allow AI agents to securely trigger actions and fulfill requests across core banking systems. Develop automated evaluation frameworks and LLMOps workflows for deterministic and generative conversation monitoring at scale. Provision and manage high performance AI infrastructure across both GCP (VertexAI) and Azure environments. What You'll Need Minimum 2+ years of experience building and deploying production grade LLM applications (moving beyond Jupyter notebooks). Expert level Python literacy with deep knowledge of AgenticAI tools such as Langgraph, ADK, and CrewAI. Proven experience in AI Engineering, including RAG pipelines, Prompt Engineering, and VertexAI. Strong background in LLMOps, including runtime evaluation, monitoring, and performance tuning. Knowledge of Responsible AI practices, ethics, and the development of safety guardrails is highly desirable. What's On Offer Long term stable contract within a high impact Conversational Banking Lab. Hybrid working model (3 days in a modern London hub) offering the perfect balance of collaboration and focus. Opportunity to work with cutting edge multi cloud AI stacks across both Azure and GCP. A fast paced, Agile environment where your AI designs go straight into the hands of customers. Apply Apply via Haystack today! Freelance data hiring powered by an engaged, trusted community-not a CV database.
Mar 17, 2026
Full time
Overview - Featured Role Apply direct with Data Freelance Hub This role is for a Data & AI Scientist with a long term contract in London, offering a pay rate of "unknown." Key skills include advanced Python, AgenticAI tools, and experience with LLM applications. Hybrid work model; financial industry experience preferred. We are working with a leading edge financial innovation lab shaping the future of conversational banking. As a Data & AI Scientist, you will be at the forefront of the generative revolution, building production grade agentic workflows that redefine how customers interact with global banking systems. You will leverage advanced Python engineering and multi cloud infrastructure (Azure & GCP) to transition experimental AI into high impact, autonomous customer solutions. Responsibilities Architect and deploy production ready AgenticAI solutions using Langgraph, CrewAI, and multi agent frameworks. Design and scale RAG pipelines and generative search experiences, evolving standard vector search into fully conversational interfaces. Build robust integration patterns that allow AI agents to securely trigger actions and fulfill requests across core banking systems. Develop automated evaluation frameworks and LLMOps workflows for deterministic and generative conversation monitoring at scale. Provision and manage high performance AI infrastructure across both GCP (VertexAI) and Azure environments. What You'll Need Minimum 2+ years of experience building and deploying production grade LLM applications (moving beyond Jupyter notebooks). Expert level Python literacy with deep knowledge of AgenticAI tools such as Langgraph, ADK, and CrewAI. Proven experience in AI Engineering, including RAG pipelines, Prompt Engineering, and VertexAI. Strong background in LLMOps, including runtime evaluation, monitoring, and performance tuning. Knowledge of Responsible AI practices, ethics, and the development of safety guardrails is highly desirable. What's On Offer Long term stable contract within a high impact Conversational Banking Lab. Hybrid working model (3 days in a modern London hub) offering the perfect balance of collaboration and focus. Opportunity to work with cutting edge multi cloud AI stacks across both Azure and GCP. A fast paced, Agile environment where your AI designs go straight into the hands of customers. Apply Apply via Haystack today! Freelance data hiring powered by an engaged, trusted community-not a CV database.
- Featured Role Apply Direct with Data Freelance Hub This role is a part-time Machine Learning Engineer position, offering $50-$100/hour for 30+ hours/week, primarily weekdays. Requirements include an active or recently graduated PhD, expertise in data science, machine learning, and Python, along with strong analytical skills. Location: Remote. United Kingdom. Position: PhD RaterType: Part-TimeCompensation: $50-$100/hourLocation: RemoteCommitment: 30+ hours/week (primarily weekdays) Responsibilities Design challenging, real-world STEM benchmark problems in domains such as data science, machine learning, finance, and software engineering. Implement tasks within an agentic development environment using Python. Create reproducible problem setups with clear specifications and executable tests. Evaluate and analyze AI model behavior, including reasoning traces and agent workflows. Diagnose reasoning failures, logic gaps, and problem-solving limitations in AI systems. Contribute to improving benchmark quality and evaluation frameworks for frontier AI models. Requirements Active or recently graduated PhD. Deep expertise in data science, machine learning, finance, and/or Python-based software development. Strong research background in advanced STEM topics. Ability to commit reliably for 30+ hours per week. Demonstrated technical output such as high-quality open-source contributions or research work. Ability to analyze agent behavior traces and diagnose failures beyond surface-level errors. Application Process Upload resume Interview Submit form Freelance data hiring powered by an engaged, trusted community - not a CV database.
Mar 13, 2026
Full time
- Featured Role Apply Direct with Data Freelance Hub This role is a part-time Machine Learning Engineer position, offering $50-$100/hour for 30+ hours/week, primarily weekdays. Requirements include an active or recently graduated PhD, expertise in data science, machine learning, and Python, along with strong analytical skills. Location: Remote. United Kingdom. Position: PhD RaterType: Part-TimeCompensation: $50-$100/hourLocation: RemoteCommitment: 30+ hours/week (primarily weekdays) Responsibilities Design challenging, real-world STEM benchmark problems in domains such as data science, machine learning, finance, and software engineering. Implement tasks within an agentic development environment using Python. Create reproducible problem setups with clear specifications and executable tests. Evaluate and analyze AI model behavior, including reasoning traces and agent workflows. Diagnose reasoning failures, logic gaps, and problem-solving limitations in AI systems. Contribute to improving benchmark quality and evaluation frameworks for frontier AI models. Requirements Active or recently graduated PhD. Deep expertise in data science, machine learning, finance, and/or Python-based software development. Strong research background in advanced STEM topics. Ability to commit reliably for 30+ hours per week. Demonstrated technical output such as high-quality open-source contributions or research work. Ability to analyze agent behavior traces and diagnose failures beyond surface-level errors. Application Process Upload resume Interview Submit form Freelance data hiring powered by an engaged, trusted community - not a CV database.