Research Engineer, Machine Learning (Reinforcement Learning)

Anthropic; San Francisco (CA); Hybrid; USD 500,000 - 850,000; Full time

Job summary

Anthropic is seeking a Research Engineer specializing in Reinforcement Learning to advance the capabilities and safety of large language models. This role involves collaboration with researchers and engineers to implement innovative approaches, build scalable systems, and enhance performance through optimization. Candidates should have proficiency in Python, experience with machine learning frameworks, and strong communication skills. The position offers a salary range of $500,000 to $850,000 annually and requires a Bachelor's degree or equivalent experience.

Qualifications

• Experience with machine learning research.
• Experience with reinforcement learning techniques.
• Familiarity with LLM architectures.

Responsibilities

• Collaborate on advancing large language models.
• Build scalable reinforcement learning infrastructure.
• Optimize and benchmark performance across systems.

Skills

Proficient in Python

Machine learning frameworks (PyTorch, TensorFlow, JAX)

Systems design and communication skills

Async/concurrent programming

Code quality and testing

Performance optimization

Education

Bachelor’s degree or equivalent

Tools

Kubernetes

Rust

C++

Job description

About the Role

As a Research Engineer within Reinforcement Learning, you will collaborate with a diverse group of researchers and engineers to advance the capabilities and safety of large language models. This role blends research and engineering responsibilities, requiring you to implement novel approaches, contribute to research directions, and build scalable systems.

Representative Projects

• 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 reinforcement learning agents.
• Drive performance improvements across our stack through profiling, optimization, and benchmarking.
• Collaborate across research and engineering teams 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 machine learning 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.
• Are passionate about the potential impact of AI and are committed to developing 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 and/or C++.

Strong Candidates Need Not Have

• Formal certifications or education credentials.
• Academic research experience or publication history.

Compensation

Annual Salary: $500,000—$850,000 USD.

Logistics

Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience.
Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience.
Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position.
Location: Expect all staff to be in one of our offices at least 25% of the time; some roles may require more on-site presence.
Visa sponsorship: We sponsor visas when possible.