Research Engineer, Machine Learning (Reinforcement Learning)

• Collaborate with researchers and engineers to advance the capabilities and safety of large language models through reinforcement learning research and engineering. • Architect and optimise core RL infrastructure from training abstractions to distributed experiment management across GPU clusters. • Design, implement, and test novel training environments, evaluations, and methodologies for RL agents that push the state of the art for the next generation of models. • Work on creating agentic models via tool use for open-ended tasks such as computer use, autonomous software generation, and improved mathematical reasoning. • Be based at least 25% of the time in Anthropic's London office.

• Be proficient in Python and async/concurrent programming with frameworks such as Trio. • Have experience with machine learning frameworks including PyTorch, TensorFlow, or JAX. • Have industry experience in machine learning research. • Be able to balance research exploration with engineering implementation. • Care about code quality, testing, and performance. • Have strong systems design and communication skills. • Be passionate about the potential impact of AI and committed to developing safe and beneficial systems.

• Have familiarity with LLM architectures and training methodologies. • Have experience with reinforcement learning techniques and environments. • Have experience with virtualisation and sandboxed code execution environments. • Have experience with Kubernetes, distributed systems, or high-performance computing. • Have experience with Rust and/or C++.

• Architect and optimise core RL infrastructure including training abstractions and distributed experiment management. • Design and implement novel training environments, evaluations, and RL methodologies. • Drive performance improvements through profiling, optimisation, and benchmarking. • Implement efficient caching solutions and debug distributed systems to accelerate training and evaluation. • Collaborate across research and engineering teams to develop automated testing frameworks, clean APIs, and scalable infrastructure. • Contribute to both research direction and implementation of novel approaches.

• Earn £260,000–£630,000 per year. • Receive visa sponsorship — Anthropic retains an immigration lawyer and makes every reasonable effort to support visa applications. • Access optional equity donation matching, generous vacation and parental leave, and flexible working hours. • Work at one of the world's leading AI safety research organisations on cutting-edge RL research that ships into deployed Claude models.

Anthropic is a public benefit corporation headquartered in San Francisco, with a mission to create reliable, interpretable, and steerable AI systems. The Reinforcement Learning teams lead Anthropic's RL research and development, having contributed to all Claude models with significant impact on the autonomy and coding capabilities of Claude Sonnet 4.5 and Opus 4.5. The London team sits at the intersection of cutting-edge research and engineering excellence.