Software Engineer - AI / ML / Python (Lead Level)

Bloomsbury Square, London, United Kingdom

Job Title:

Software Engineer - AI / ML / Python (Lead Level)

Location:

London, United Kingdom (Hybrid - 2-3 days onsite per week)

Contract Type:

Contract (6 months, with extension likely)

Start Date:

Immediate / Within 2-4 weeks

Job Description:

We are seeking an experienced and highly motivated Lead Software Engineer with deep expertise in Artificial Intelligence (AI), Machine Learning (ML), and Python development to lead the design, development, and deployment of intelligent systems and data-driven applications for a leading client in London.

The ideal candidate will have a strong background in AI/ML frameworks, scalable system design, and Python-based development, along with leadership experience in agile teams.

Key Responsibilities:

Lead the architecture and development of AI/ML solutions, ensuring scalable and efficient design.

Design and implement ML models and algorithms (classification, regression, NLP, etc.) using modern frameworks.

Collaborate with data scientists, engineers, and product teams to transform prototypes into production-grade applications.

Optimize model performance and manage end-to-end ML lifecycle (data ingestion, training, evaluation, deployment).

Mentor junior engineers and contribute to code reviews, best practices, and technical decision-making.

Implement MLOps pipelines for continuous training, deployment, and monitoring of models.

Ensure compliance with data privacy and security regulations (GDPR, etc.).

Required Skills & Qualifications:

Bachelor's or Master's degree in Computer Science, Engineering, AI, or related field.

7+ years of professional software development experience, with at least 3 years in AI/ML.

Strong proficiency in Python, including libraries like NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch.

Solid understanding of ML algorithms, NLP, deep learning, and statistical methods.

Experience with Docker, Kubernetes, and cloud platforms like AWS / Azure / GCP.

Hands-on experience with MLOps tools (MLflow, SageMaker, Kubeflow, etc.) and version control systems.

Strong knowledge of APIs, microservices architecture, and CI/CD pipelines.

Proven experience in leading teams, managing stakeholders, and delivering end-to-end AI/ML projects.

Nice to Have:

Exposure to LLMs (Large Language Models), generative AI, or transformer architectures.

Experience with data engineering tools (Spark, Airflow, Snowflake).

Prior experience in fintech, healthtech, or similar domains is a plus.