Research Engineer, Machine Learning (Reinforcement Learning)

• Collaborate with a diverse group of researchers and engineers within Anthropic's Reinforcement Learning teams to advance the capabilities and safety of large language models. • Blend research and engineering responsibilities, implementing novel approaches and contributing to research direction across fundamental RL research, agentic models, computer use, autonomous software generation, and reasoning. • Work on teams that have contributed to all Claude models with significant impacts on the autonomy and coding capabilities of Claude Sonnet 4.5 and Opus 4.5.

• Be proficient in Python and async/concurrent programming with frameworks like Trio. • Have experience with machine learning frameworks such as PyTorch, TensorFlow, or JAX. • Have industry experience in machine learning research. • Be able to balance research exploration with engineering implementation. • Enjoy pair programming. • 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. • Have experience with distributed systems or high-performance computing. • Have experience with Rust and/or C++.

• Architect and optimise core reinforcement learning infrastructure from clean training abstractions to distributed experiment management across GPU clusters, helping scale systems to handle increasingly complex research workflows. • Design, implement, and test novel training environments, evaluations, and methodologies for reinforcement learning agents that push the state of the art for the next generation of models. • Drive performance improvements across the stack through profiling, optimisation, and benchmarking, implementing efficient caching solutions and debugging distributed systems to accelerate training and evaluation workflows. • Collaborate across research and engineering teams to develop automated testing frameworks, design clean APIs, and build scalable infrastructure that accelerates AI research.

• Receive an annual salary of £260k–£630k GBP. • Work from the London office with a hybrid policy requiring at least 25% office time. • Receive visa sponsorship with every reasonable effort made and an immigration lawyer retained to help. • Receive competitive compensation and benefits with optional equity donation matching. • Receive generous vacation and parental leave. • Enjoy flexible working hours.

Anthropic's mission is to create reliable, interpretable, and steerable AI systems that are safe and beneficial for users and society. The company is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. Anthropic is a public benefit corporation headquartered in San Francisco with offices in London.