14 days ago
Base Salary
$500k - $850k/yr
Responsibilities
- Architect and optimize reinforcement learning infrastructure, including training abstractions and distributed experiment management across GPU clusters.
- Design, implement, and test training environments, evaluations, and methodologies for reinforcement learning agents.
- Improve system performance through profiling, optimization, benchmarking, caching, and distributed-systems debugging.
- Develop automated testing frameworks, clean APIs, and scalable infrastructure for AI research.
- Collaborate with researchers and engineers to advance agentic models, reasoning capabilities, computer use, and autonomous software generation.
Requirements
- Proficiency in Python and asynchronous or concurrent programming, including frameworks such as Trio.
- Experience with machine learning frameworks such as PyTorch, TensorFlow, or JAX.
- Industry experience in machine learning research and the ability to combine research exploration with engineering implementation.
- Strong systems design, communication, code quality, testing, and performance skills.
- Familiarity with LLM architectures, training methodologies, reinforcement learning techniques and environments, virtualization, sandboxed code execution, Kubernetes, distributed systems, or high-performance computing is preferred.
- Experience with Rust or C++ is preferred.
- Formal certifications, academic research experience, and publication history are not required.
- A bachelor's degree or equivalent combination of education, training, and/or experience in a relevant field is required.
Benefits
- Annual compensation range of $500,000–$850,000 USD.
- Hybrid policy requiring staff to work from an office at least 25% of the time, with some roles requiring more office time.
- Visa sponsorship may be available, with immigration-lawyer support.
- Competitive benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and an office collaboration space.
Tech Stack
Categories
AI ResearchML Engineering
About Anthropic
We're an AI research company that builds reliable, interpretable, and steerable AI systems. Our first product is Claude, an AI assistant for tasks at any scale. Our research interests span multiple areas including natural language, human feedback, scaling laws, reinforcement learning, code generation, and interpretability.