RL Research Engineer - Scalable, Safe AI Systems

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

Benefits offered by this job

Competitive compensation

Equity donation matching

Generous vacation and parental leave

Flexible working hours

Office space

Job summary

Anthropic in San Francisco seeks a Research Engineer in Reinforcement Learning to advance the capabilities and safety of large language models, blending research and engineering. You will implement novel approaches, build scalable infrastructure, and develop prototype tools for internal use, productivity, and evaluation.

Strong candidates have Python, ML frameworks, and experience in ML research. The role offers a hybrid work arrangement with a focus on collaboration and impact.

Qualifications

• Proficient in Python and async/concurrent programming with frameworks like Trio.
• Experience with machine learning frameworks (PyTorch, TensorFlow, JAX).
• Industry experience in machine learning research.

Responsibilities

• Architect and optimize core reinforcement learning infrastructure and experiment management.
• Design and test new training environments and evaluation methods for RL agents.
• Collaborate across research and engineering to build scalable AI research infrastructure.

Skills

Python

Async programming

Pair programming

Communication skills

Education

Bachelor's degree

Tools

PyTorch

TensorFlow

JAX

Kubernetes

Rust

C++

Virtualization

Job description

Anthropic in San Francisco seeks a Research Engineer in Reinforcement Learning to advance the capabilities and safety of large language models, blending research and engineering. You will implement novel approaches, build scalable infrastructure, and develop prototype tools for internal use, productivity, and evaluation.

Strong candidates have Python, ML frameworks, and experience in ML research. The role offers a hybrid work arrangement with a focus on collaboration and impact.