ML Infrastructure Engineer Jobs

• London
• Hybrid · 1 day in office
• £325,000 – £485,000 pa
• Lead

Sets technical direction for agent-driven compute cluster lifecycle management, covering provisioning, updates and decommissioning across major clouds and own datacenters. Partners with security, research and cloud providers on secure-by-default, high-bandwidth, fault-tolerant clusters, and mentors engineers while owning multi-quarter strategy.

Kubernetes · Terraform · AWS +7

• 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

• United Kingdom
• Remote
• Mid-level
• Permanent

Owns the data infrastructure behind frontier AI models, building large-scale pipelines for collecting, filtering and transforming training datasets. Also trains classifiers, quality filters and labeling models, and designs curation strategies like deduplication and quality scoring. Fully remote, with tooling work letting researchers explore and train on massive datasets.

Kubernetes

• London
• Hybrid · 3 days in office
• Lead

Builds and evolves a large-scale ML infrastructure platform that supports training and deploying novel models across vast compute and data pools. Works closely with engineering, research and product teams, and explores deploying agents to improve platform robustness. Requires strong Python and experience scaling complex systems, with ML or Kubernetes exposure a plus.

Kubernetes · Google Cloud Platform · GCP

• London
• Hybrid
• Permanent

Builds and optimizes the compute platform behind frontier AI, spanning bare-metal automation, Kubernetes scheduling, high-performance networking, storage, and fleet health. Engineers move across software, hardware, and networking layers, profiling training workloads and improving NCCL, RDMA, and GPU efficiency. Hiring is general across Compute Infrastructure, with teams matched to candidate strengths.

Kubernetes · NCCL · RDMA +4

• London
• Hybrid
• Mid-level
• Permanent

Builds and operates cloud infrastructure, automation and deployment systems, primarily on Azure, using Terraform and Ansible for infrastructure as code. Supports CI/CD pipelines, containerised workloads, monitoring, observability and cost optimisation, and handles incident response and root-cause analysis. Works closely with engineering teams to improve the developer experience.

Azure · AWS · GCP +4

• London
• Mid-level
• Permanent

Backend engineering role focused on the systems that keep ChatGPT reliable at scale, spanning shared services, APIs, asynchronous processing and infrastructure migrations. Engineers write production code, own rollout and rollback, and improve monitoring and diagnostics, with on-call and incident response duties. Distinct for its close coupling of infrastructure work to a high-traffic consumer product.

ChatGPT · APIs · Cloud Infrastructure +2

• 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