Research Engineer, Machine Learning (Reinforcement Learning)

Anthropic's mission is to create reliable, interpretable, and steerable AI systems. We are a public benefit corporation headquartered in San Francisco, working as a single cohesive team on large-scale research efforts.

As a Research Engineer within Reinforcement Learning, you will collaborate with researchers and engineers to advance the capabilities and safety of large language models. This role blends research and engineering, requiring you to implement novel approaches and contribute to research direction. You'll work on fundamental RL research, creating agentic models via tool use for tasks like computer use and autonomous software generation, improving reasoning abilities, and developing prototypes.

• Architect and optimize core reinforcement learning infrastructure, from clean training abstractions to distributed experiment management across GPU clusters.
• Design, implement, and test novel training environments, evaluations, and methodologies for RL agents.
• Drive performance improvements through profiling, optimization, and benchmarking.
• Implement efficient caching solutions and debug distributed systems.
• Collaborate to develop automated testing frameworks, design clean APIs, and build scalable infrastructure.

You may be a good fit if you are proficient in Python and async/concurrent programming with frameworks like Trio, have experience with machine learning frameworks (PyTorch, TensorFlow, JAX), have industry experience in ML research, can balance research exploration with engineering implementation, enjoy pair programming, care about code quality, testing, and performance, have strong systems design and communication skills, and are passionate about safe AI.

Strong candidates may have familiarity with LLM architectures, RL techniques, virtualization, Kubernetes, distributed systems, and Rust/C++.

Annual Salary: £260,000—£630,000 GBP

Anthropic offers competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space.

Deadline: None, rolling basis. Visa sponsorship is available. Apply via the provided link.