Research Engineer, Machine Learning (Reinforcement Learning)
Anthropic · San Francisco, CA | New York City, NY · AI Research & Engineering
About this role
Anthropic is hiring a mid-level Research Scientist in the machine learning function based in San Francisco, CA | New York City, NY. The posting calls out experience with Python, Rust, Kubernetes, TensorFlow. Compensation is listed at $500,000–$850,000 per year.
- Role
- Research Scientist
- Function
- machine learning
- Level
- mid
- Track
- Individual contributor
- Employment
- Full-time
- Location
- San Francisco, CA | New York City, NY
- Department
- AI Research & Engineering
More roles at Anthropic
Job description
from Anthropic careersAbout Anthropic
Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.
About the teams
Our Reinforcement Learning teams lead Anthropic's reinforcement learning research and development, playing a critical role in advancing our AI systems. We've contributed to all Claude models, with significant impacts on the autonomy and coding capabilities of Claude Sonnet 4.5 and Opus 4.5. Our work spans several key areas:
- Developing systems that enable models to use computers effectively
- Advancing code generation through reinforcement learning
- Pioneering fundamental RL research for large language models
- Building scalable RL infrastructure and training methodologies
- Enhancing model reasoning capabilities
We collaborate closely with Anthropic's alignment and frontier red teams to ensure our systems are both capable and safe. We partner with the applied production training team to bring research innovations into deployed models, and are dedicated to implement our research at scale. Our Reinforcement Learning teams sit at the intersection of cutting-edge research and engineering excellence, with a deep commitment to building high-quality, scalable systems that push the boundaries of what AI can accomplish.