Anthropic is seeking a Research Engineer to advance the capabilities and safety of large language models through reinforcement learning research and development.
Requirements
- Proficiency in Python and async/concurrent programming with frameworks like Trio
- Experience with machine learning frameworks (PyTorch, TensorFlow, JAX)
- Industry experience in machine learning research
- 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
Responsibilities
- Architect and optimize core reinforcement learning infrastructure
- Design, implement, and test novel training environments, evaluations, and methodologies for reinforcement learning agents
- Drive performance improvements across the stack through profiling, optimization, and benchmarking
- Implement efficient caching solutions and debug distributed systems to accelerate both training and evaluation workflows
- Collaborate across research and engineering teams to develop automated testing frameworks, design clean APIs, and build scalable infrastructure
- Develop prototypes for internal use, productivity, and evaluation
- Advance code generation through reinforcement learning
Other
- At least a Bachelor's degree in a related field or equivalent experience
- Location-based hybrid policy: currently, we expect all staff to be in one of our offices at least 25% of the time
- Visa sponsorship: we do sponsor visas, but we aren't able to successfully sponsor visas for every role and every candidate
- Strong systems design and communication skills
- Care about code quality, testing, and performance
- Enjoy pair programming
- Passionate about the potential impact of AI and committed to developing safe and beneficial systems
