Machine Learning Jobs in London

• London
• Hybrid
• Senior
• Permanent

Lead the design, build and deployment of production-grade ML and software systems for clients across pharma, academia and MedTech. The role blends hands-on Python and cloud engineering with architecture decisions, client-facing technical advisory and mentoring junior engineers. Work spans scalable infrastructure, container orchestration and embedding best practices for deploying machine learning at scale.

AWS · Azure · GCP +2

• London
• Hybrid
• Senior
• Permanent

Lead high-impact AI safety projects for national security and frontier labs, inventing novel evaluation frameworks and designing robust software architectures. Mentor technical team members, partner with commercial teams on scoping, and advance the science of AI evaluations through research and public speaking. Combines hands-on Python data science with project leadership in a high-stakes, mission-driven environment.

NumPy · Pandas · Inspect AI +1

• London
• Hybrid
• Senior

Architect, deploy and support machine learning and GenAI solutions on AWS as part of an AI Enablement team, building ML pipelines, monitoring and infrastructure at scale. The role combines platform engineering with MLOps, using Terraform, Jenkins, Kubernetes and SageMaker to productionise data science models with CI/CD, versioning and security rigour.

AWS · Terraform · Jenkins +7

• London
• Senior

Optimise machine learning model performance across training and inference in a tech-centric prop trading fund. Work spans CUDA and GPU-level tuning, low-latency real-time inference, high-throughput research inference, plus storage, networking and host-level systems concerns within a growing ML team.

CUDA · PTX · SASS +7

• London
• Hybrid · 3 days in office
• Mid-level

Join the model performance and scaling team to implement and optimize LLM post-training methods on frontier models, working with research teams to turn new methods into production systems. The role focuses on distributed training and inference performance, low-precision methods, and frameworks like JAX or PyTorch, in a hybrid London setting.

JAX · PyTorch · NCCL +5

• London
• Hybrid · 3 days in office
• Senior
• Permanent

Senior technical owner for a portfolio of public sector customers, shaping AI strategy from pre-sales discovery through production adoption. Owns the technical account plan across ChatGPT Enterprise, the OpenAI API, Codex and agentic solutions, designing architectures covering models, data, integration, security and governance while coordinating specialists across deployment, product and partners.

ChatGPT Enterprise · OpenAI API · Codex +1

• London
• £600 – £750 pd
• Mid-level
• Contract

Develops and deploys machine learning models and data pipelines that shape decision-making, customer service and business performance. Works closely with ML and software engineers on integration and coding standards, and communicates findings to technical and non-technical stakeholders. Retail context with scope for personalisation, recommendation and experimentation work.

• London
• Hybrid
• Mid-level
• Permanent

Builds full-stack geospatial services in Python and TypeScript, plus PySpark and Databricks pipelines that enrich fleet data with road-network and mapping information at global scale. Owns route-planning applications, map data preparation for training and simulation, and deployment on Azure and Kubernetes end to end.

Databricks · Mapbox · TomTom +10

• London
• Hybrid
• Mid-level · manages people
• Permanent

Lead a London-based team building the on-vehicle experiment platform that lets researchers deploy driving models to vehicles, run experiments and collect training data. You own people, roadmap and OEM partner relationships while staying hands-on with embedded Linux, C++/Python and over-the-air deployment across vehicle fleets.

NVIDIA Jetson · NVIDIA DRIVE · QNX +4

• London
• Hybrid
• Senior
• Permanent

Architect novel generative models to design functional proteins, working in an interdisciplinary team of ML researchers, protein engineers and biologists. The role spans data curation, evaluation metrics, rapid prototyping, cloud training and inference optimisation, plus planning wet lab testing campaigns with the bio team.

• London
• Hybrid · 2–3 days in office

Owns the infrastructure behind speech AI models, building scalable data pipelines for ingesting, transforming and validating large training datasets, plus web scraping and data acquisition tooling. Also operates the platform for training, evaluating and serving models, optimising GPU utilisation, scheduling and observability across distributed systems.

Docker · Kubernetes

• London
• Hybrid · 2–3 days in office
• Senior

Join the Modelling Team to train large self-supervised and transformer-based speech models, ensuring their deployment into production. The role involves complex R&D, distributed training, inference optimisation, cross-department collaboration and mentoring, with a hybrid pattern of 2-3 office days per week.

GQA · KV-Caching · Flash Attention +2

• London
• Hybrid · 3 days in office
• Mid-level
• Permanent

Join OpenAI's Training team in London to push the frontier of LLM development for flagship models, enhancing intelligence, efficiency, and adding new capabilities. The role involves designing and scaling new architectures, running experiments, debugging regressions, and optimizing model and computational performance, with a hybrid schedule of three days in the office per week.

• London
• On-site
• Senior
• Permanent

Builds generative and predictive models of cellular behaviour from high-content imaging, curating cell painting and brightfield datasets and designing evaluation that separates biological signal from technical artefact. Partners closely with ML scientists and wet lab assay teams, linking imaging readouts to single-cell and perturbation data in a matrixed TechBio environment.

NumPy · pandas · Polars +6

• London
• Hybrid · 1–2 days in office
• £75,000 – £85,000 pa
• Senior

Own the ML Ops function within a growing AI and data organisation, building and maintaining production-grade ML orchestration pipelines with Dagster, Airflow or Prefect. Deploy, monitor and scale ML and LLM-powered services on Kubernetes using Terraform or Bicep, with strong CI/CD and observability practices, working closely with data scientists and client-facing teams.

Dagster · Airflow · Prefect +5