Machine Learning Jobs in Woking

• London
• Remote
• Temporary

A four-month, full-time research fellowship focused on empirical AI projects in either ML systems and performance or reinforcement learning. Fellows work with external infrastructure like open-source models and public APIs, receive direct mentorship from Anthropic researchers, and aim to produce a public output such as a paper submission.

Claude

• London
• Hybrid · 1 day in office
• £225,000 – £255,000 pa
• Mid-level

Partner-facing role embedding with nonprofits, research institutes and academic medical centres to apply Claude to clinical development for rare and neglected diseases. You'll design and review trial protocols, build tools for drug repurposing from literature, omics and patient data, and create reusable infrastructure like MCP servers and benchmarks.

Claude · MCP

• London
• £25,000 – £45,000 pa
• Entry level

A self-paced traineeship taking complete beginners through AI fundamentals, Python, data handling, machine learning and Git/GitHub, with Microsoft AI-900 certification and two tutor-assigned industry projects. On completion, candidates are placed into a Junior AI Engineer role with a partner employer within 20 miles of their location.

Microsoft AI-900 · Azure AI Fundamentals · Git +1

• Norwich
• £25,000 – £45,000 pa
• Entry level

A self-paced traineeship taking complete beginners through AI fundamentals, Python, data handling, machine learning and Git/GitHub, with Microsoft AI-900 certification and two tutor-assigned industry projects. On completion, candidates are placed into a Junior AI Engineer role with a partner employer within 20 miles of their location.

Azure · Microsoft AI-900 · Git +1

• New York, United States
• Hybrid
• US$150,000 – US$250,000 pa
• Lead

Customer-facing role owning the full customer journey, from onboarding and change management to roadmap planning and contract preparation. Works alongside simulation, software, ML engineers and data scientists to translate industrial engineering challenges into product opportunities, tracking engagement and measuring value. Hybrid role based in Manhattan with remote flexibility.

• Cambridge, United States
• Hybrid · 3 days in office
• Senior · manages people

Lead medicinal chemistry efforts on drug discovery projects, guiding them from initiation to clinical candidate selection as a Project Lead or Medicinal Chemistry Lead. Partner closely with ML scientists to refine AI models, manage CRO resources, and generate IP, with some roles line-managing 2-4 chemists.

AlphaFold

• London
• Hybrid · 3 days in office
• Lead

Lead medicinal chemistry strategy across drug discovery programmes, from hit identification through lead optimisation to candidate nomination, while working hands-on as an individual contributor. Partner closely with AI/ML platform teams to shape predictive models, manage CRO resources and represent the company externally.

AlphaFold

• New York, United States
• Hybrid
• Lead

Lead the ML approach to manufacturing and MRO data, taking models from design through deployment in customer production environments across cloud, on-prem and edge. Work with sparse, drifting sensor and process data, fusing physics simulation with shop-floor measurement, and set uncertainty quantification and validation standards. Requires travel to customer sites 3-4 weeks per quarter and mentoring of engineers and data scientists.

PyTorch · Pandas · FastAPI +2

• Switzerland
• Remote
• Senior
• Permanent

Builds production-quality C++ components, APIs and integrations for NVIDIA's AI-powered developer-tools ecosystem, connecting native C++ tools to retrieval and agentic services via Python, MCP and REST. Involves architecting performance-sensitive systems, contributing to agentic workflows and mentoring engineers.

MCP · REST APIs · Python +2

• London
• On-site
• Lead · manages people

Lead a team of six applied scientists building vision-language models for document data extraction and sub-5MB models that run on mobile devices, using distillation and quantisation. The role is roughly 50% hands-on, contributing to dataset creation, training and evaluation code in Python and PyTorch, while setting the roadmap with product and engineering and publishing research.

AWS · Encord · Ray +3

• London
• Hybrid
• Senior

Customer-facing role building and productionizing data and AI solutions on the Databricks platform, owning architecture and design decisions for end-to-end systems spanning data engineering, ML/AI and application development. Embeds with client teams from technical ICs to executives, delivering production-grade systems, reference architectures and reusable accelerators, with around 20% travel to customer sites.

Databricks · AWS · Azure +7

• London
• Hybrid
• £70,000 – £90,000 pa
• Senior
• Permanent

Designs and builds modern machine learning and AI services within a collaborative data team, developing and optimising data pipelines across a cloud analytics platform. Works with PySpark, Python, SQL, Databricks or Snowflake on AWS, supporting ML and GenAI infrastructure in agile squads.

Databricks · Snowflake · AWS +7

• London
• Mid-level

You will own and grow one of Databricks' most strategic Manufacturing accounts, co-developing a business plan with ecosystem partners to exceed quarterly and annual usage and booking goals. The role involves leading complex sales campaigns, proving out big data and AI use cases on the Data Intelligence Platform, and co-selling with AWS, Azure, Google Cloud and Global Solution Integrators while engaging C-level executives.

Databricks · AWS · Azure +7

• Cambridge
• Hybrid
• Mid-level

Design and build LLM-agentic workflows that reason over knowledge graphs, proprietary methods and scientific literature to generate and triage therapeutic hypotheses for rare diseases. Works closely with drug discovery scientists in a cross-functional team, using Python, ADK and AgentSpace, with scope to own workflows end to end.

Python · ADK · AgentSpace

• Eastleigh
• Hybrid
• £50,000 – £70,000 pa
• Permanent

Builds and supports data products on a modern cloud data platform, developing and optimising pipelines and integrating varied sources with strong quality standards. Works in agile squads with data and AI engineers, scientists and architects, using PySpark, Python, SQL and Databricks or Snowflake on AWS, plus Airflow, Terraform and Kubernetes.

Databricks · Snowflake · AWS +7