Research Engineer, Machine Learning (Reinforcement Learning)

Anthropic; Greater London; Hybrid; GBP 260,000 - 630,000; Full time

Job summary

Anthropic is seeking a Research Engineer specializing in Reinforcement Learning to advance large language model capabilities. This role involves collaborative research and engineering, focused on optimizing core reinforcement learning infrastructure and driving performance through novel methodologies. We're looking for candidates proficient in Python, with strong experience in machine-learning frameworks and systems design. The position offers a salary range of £260,000–£630,000 GBP and requires a Bachelor's degree or equivalent, along with a commitment to AI safety and benefits.

Qualifications

• Proficient in Python and async/concurrent programming frameworks like Trio.
• Experience with machine‑learning frameworks (PyTorch, TensorFlow, JAX).
• Can balance research exploration with engineering implementation.
• Strong systems design and communication skills.

Responsibilities

• Collaborate with researchers and engineers to advance capabilities of large language models.
• Implement novel approaches while contributing to research direction.
• Architect and optimize core reinforcement learning infrastructure.
• Drive performance improvements through profiling and optimization.

Skills

Python

Async/concurrent programming frameworks

Machine-learning frameworks (PyTorch, TensorFlow, JAX)

Strong systems design

Communication skills

Education

Bachelor’s degree or equivalent

Tools

Kubernetes

Distributed systems

Rust or C++

Job description

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.