About Anthropic
Anthropic’s mission is to create reliable, interpretable, and steerable AI systems that are safe and beneficial for users and society.
About the Role
As a Research Engineer within Reinforcement Learning, you will collaborate with researchers and engineers to advance the capabilities and safety of large language models. The role blends research and engineering: implement novel approaches while contributing to research direction.
Representative Projects
- Architect and optimize core reinforcement learning infrastructure, including training abstractions and distributed experiment management across GPU clusters.
- Design, implement, and test novel training environments, evaluations, and methodologies for reinforcement learning agents.
- Drive performance improvements through profiling, optimization, and benchmarking; implement efficient caching and debug distributed systems.
- Collaborate with research and engineering teams to develop automated testing frameworks, clean APIs, and scalable infrastructure.
You May Be a Good Fit If
- Proficient in Python and async/concurrent programming frameworks like Trio.
- Experience with machine‑learning frameworks (PyTorch, TensorFlow, JAX).
- Industry experience in ML research.
- Can balance research exploration with engineering implementation.
- Enjoy pair programming.
- Care about code quality, testing, and performance.
- Strong systems design and communication skills.
- Passionate about AI impact and committed to safe and beneficial systems.
Strong Candidates May Also Have
- Familiarity with LLM architectures and training methodologies.
- Experience with reinforcement learning techniques and environments.
- Experience with virtualization and sandboxed code execution environments.
- Experience with Kubernetes.
- Experience with distributed systems or high‑performance computing.
- Experience with Rust or C++.
Strong Candidates Do Not Need
- Formal certifications or specific education credentials.
- Academic research experience or publication history.
Logistics
- Annual Salary: £260,000–£630,000 GBP.
- Minimum education: Bachelor’s degree or equivalent.
- Required field of study: Relevant to the role.
- Minimum years of experience: Depends on internal level.
- Location‑based hybrid policy: Staff should be in office at least 25% of time.
- Visa sponsorship: We sponsor visas when possible.
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