Discover ML job opportunities in Rotherham

Software Engineer

The Software Engineer will work on the complete development lifecycle of flight safety and navigation systems, from concept and algorithm design to system integration and testing. You will collaborate with a multidisciplinary team to deliver high-performance solutions, maintain high-quality code, and produce comprehensive documentation.

Flarebright Bicester £39,000 – £49,000 pa

On-site Permanent Clearance Required

Head of AI

As Head of AI, you will lead the development and implementation of AI strategies, governance, and capabilities at LPPA, a leading pension administration company. You will work closely with the CTO and executive team to identify and deliver AI opportunities that enhance operational efficiency, service quality, and member outcomes. Key responsibilities include building the AI team, establishing governance frameworks, and fostering AI adoption across the organization.

Local Pensions Partnership Administration Preston £90,000 – £100,000 pa

Hybrid Permanent

Research Engineer, Machine Learning (Reinforcement Learning)

Blends reinforcement learning research with engineering, building scalable RL infrastructure, distributed training across GPU clusters, and novel training environments for agentic LLMs. Involves profiling, optimization, caching, and debugging distributed systems, with close collaboration between research and production teams.

Anthropic London £260,000 – £630,000 pa

On-site Permanent

Research Engineer, Machine Learning (RL Velocity)

Builds and improves the core RL training infrastructure that researchers depend on, profiling, debugging and rearchitecting bottlenecks across the stack. Works closely with researchers and adjacent teams such as inference and sandboxing to ship tooling that speeds up training runs, spanning low-level performance work through to RL algorithms.

Anthropic London £370,000 – £630,000 pa

Hybrid Permanent

Research Engineer, Pretraining

Join the Pretraining team to develop next-generation large language models, working across model architecture, algorithms, data processing and optimizer development. You'll lead small research projects, design and analyse experiments, and scale distributed training infrastructure to thousands of GPUs, balancing research goals with practical engineering.