Machine Learning Jobs in London

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

Join the Compute Infrastructure team to keep a planet-scale GPU accelerator fleet healthy and efficient. You'll build observability and telemetry pipelines, automate recovery, hunt compute waste, and optimise accelerator utilisation for large-scale training and inference, working closely with ML infrastructure and research teams.

GCP · Kubernetes · Nvidia GPU +1

• London
• Hybrid · 3 days in office
• Lead

Technically lead the Platform group, designing, operating and refining research, development and production cloud infrastructure across GCP, Kubernetes, Docker and Terraform. The role spans core technical decisions, tooling and CI/CD processes, working closely with scientists, ML researchers and product teams, and reports directly to the Director of Engineering.

GCP · Kubernetes · Docker +7

• London
• Hybrid · 1 day in office
• £325,000 – £395,000 pa
• Senior

Builds foundational infrastructure for AI safety, oversight and intervention, including data storage, metrics and evaluation systems, and tooling for human and agentic review. The role also involves running these systems day to day and building multi-layered, real-time defenses against misuse at scale.

Claude Code

• London
• Hybrid · 1 day in office
• £260,000 – £630,000 pa
• Mid-level

Blends research and engineering to advance reinforcement learning for large language models, building agentic capabilities like computer use and autonomous code generation. Involves architecting distributed RL training infrastructure across GPU clusters, designing novel training environments and evaluations, and profiling and optimizing the stack. Works closely with alignment, red team, and production training groups, with a strong pair-programming culture.

PyTorch · TensorFlow · JAX +3

• London
• On-site
• Entry level
• Permanent

Interns own the full lifecycle of their code, from design through deployment and operations, building scalable services on cross-disciplinary teams. They use GenAI and AI tools to boost productivity, participate in code reviews, and take on operational duties including on-call, with mentorship from a dedicated manager and mentor.

AWS

• London
• Senior
• Permanent

Lead technical direction and delivery of complex enterprise AI engagements, shaping solution roadmaps with senior stakeholders and making architecture and engineering trade-offs. Design and implement production AI solutions on AWS spanning application, data, integration, security and operations, while establishing evaluation and responsible AI controls. Also mentors, sets technical standards and builds reusable assets for the Data & AI practice.

AWS

• London
• Senior

Customer-facing engineering role owning architecture and design decisions while building production-grade data, AI and application systems on the Databricks platform. You embed with client teams, from technical ICs to executives, to scope and deliver big data and ML/AI projects, contributing reusable accelerators and product feedback. Requires hands-on coding in Python, Scala or TypeScript, deep Apache Spark and cloud expertise, with around 20% travel to customer sites.

Databricks · Apache Spark · AWS +7

• London
• Senior

Expert-level technical leader owning the most complex enterprise customer engagements, driving consumption strategy and executive relationships as the definitive technical authority. Leads multi-workload platform architectures, enterprise migrations, real-time systems and AI/ML at scale, while mentoring junior architects and orchestrating cross-functional teams. Requires deep Databricks platform expertise, Python/SQL coding proficiency and a declared technical specialisation.

Databricks · Snowflake · AWS +7

• London
• Hybrid
• Lead · manages people
• Permanent

Lead a London-based team building and operating large-scale multi-cloud, multi-region GPU compute and storage infrastructure for ML training and inference. The role is people-first: coaching engineers, hiring, and owning roadmap and delivery, while guiding Kubernetes scheduling, capacity planning and cost trade-offs across heterogeneous GPU fleets.

Kubernetes · Kueue · Nvidia Hopper +2

• London
• Hybrid
• Senior

Delivers machine learning models and analytical insights for Tesco UK Suppliers, working with transactional, shopper and clickstream data. Partners with Client Leadership teams to scope client needs and build scalable, reusable solutions across personalisation, pricing and promotions. Requires Python, SQL and statistical modelling, with PySpark advantageous.

Python · SQL · PySpark +1

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

Lead and scale a team of Applied AI Engineers supporting early-stage and high-growth startup customers from experimentation to production. You'll coach engineers on architecture, evaluations, cost optimisation and migrations, partner with Sales on competitive pursuits, and turn recurring needs into repeatable playbooks and reference architectures.

OpenAI

• London
• Hybrid
• Senior

Builds AI-powered planning systems for global warehouses and last-mile operations, developing machine learning models, optimisation algorithms and operational simulations. Takes high-impact models from prototype to monitored production, sets technical direction and mentors data scientists while working with engineers, product managers and retail partners.

BigQuery · OR-Tools · SimPy

• London
• Hybrid
• Senior

Owns the software engineering that brings data science and ML products into live production for the Autoplanner team, building AI-powered planning systems for global warehouses and last-mile assets. Works mainly in typed, well-tested Python (with some Java for OSP integration), handling cloud deployments, CI/CD, APIs, and MLOps model serving and monitoring on AWS.

AWS · GCP · Python +1

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

Lead and scale a team of Applied AI Engineers partnering with high-growth startups to move from experimentation to production on OpenAI's platform. The role blends people leadership, hands-on technical architecture guidance, and cross-functional work with Sales, Product, and Research to build repeatable deployment playbooks and reference architectures.

OpenAI

• London
• Hybrid
• Lead

Own the product strategy for the runtime that serves conversations in production, the inference layer hosting models, and the data platform feeding both. Set build-vs-buy and self-host-vs-managed direction, define evaluation frameworks for latency, throughput and cost, and partner directly with infrastructure engineering leadership on a roadmap with no customer-facing surface.

Raven