Anthropic is looking to create reliable, interpretable, and steerable AI systems, and the Tool Use team is responsible for making Claude the world's most capable, reliable, safe, and efficient model for tool use and agentic applications.
Requirements
- Strong machine learning research/applied-research experience, or a strong quantitative background such as physics, mathematics, or quant research
- Write clean, reliable code and have solid software engineering skills
- Experience with reinforcement learning techniques and environments
- Experience with language model training, fine-tuning or evaluation
- Experience building AI agents or autonomous systems
- Published influential work in relevant ML areas
- Deep expertise in a specific area (e.g., exceptional RL research, systems engineering, or mathematical foundations)
Responsibilities
- Define and pursue research agendas that push the boundaries of what's possible
- Design and implement novel reinforcement learning environments and methodologies that push the state of the art of tool use
- Build rigorous, realistic evaluations that capture the complexity of real-world tool use
- Ship research advances that directly impact millions of users
- Collaborate with other frontier research and product teams to drive fundamental breakthroughs in capabilities and safety, and work with teams to ship these into production
- Design, implement, and debug code across our research and production ML stacks
- Contribute to our collaborative research culture through pair programming, technical discussions, and team problem-solving
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 communication skills to communicate complex ideas clearly to diverse audiences
- Ability to work collaboratively with colleagues and contribute to a collaborative research culture
