Research Engineer / Scientist, Tool Use

Details

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 team

The Tool Use team within Research is responsible for making Claude the world's most capable, reliable, safe, and efficient model for tool use and agentic applications. The team focuses on foundational challenges such as tool call accuracy, complex tool use workflows, large-scale & dynamic tools, tool hallucination, tool use safety (e.g., prompt injection robustness), and efficiency. Their work supports Anthropic’s customers and internal teams building agentic capabilities in coding (including Claude Code), search & deep research, memory, and multi-agents.

Responsibilities

• Define and pursue research agendas that push the boundaries of what's possible.
• Design and implement novel reinforcement learning environments and methodologies advancing tool use.
• Build rigorous, realistic evaluations capturing the complexity of real-world tool use.
• Ship research advances impacting millions of users.
• Collaborate with frontier research and product teams to drive capability and safety breakthroughs, shipping these into production.
• Design, implement, and debug code across research and production ML stacks.
• Contribute to collaborative research culture through pair programming, discussions, and problem-solving.

Requirements

• Driven by real-world impact with excitement to see research shipped in production.
• Strong machine learning research/applied-research experience or a strong quantitative background (physics, mathematics, quantitative research).
• Write clean, reliable code with solid software engineering skills.
• Communicate complex ideas clearly to diverse audiences.
• Passion for building powerful and safe AI systems.
• Eagerness to learn and grow regardless of years of experience.

Strong candidates may also have

• Experience with reinforcement learning techniques and environments.
• Experience in language model training, fine-tuning, or evaluation.
• Experience building AI agents or autonomous systems.
• Published influential work in relevant ML areas.
• Deep expertise in specific areas such as RL research, systems engineering, or mathematical foundations.
• Experience shipping features or working closely with product teams.
• Enthusiasm for pair programming and collaborative research.

Logistics

• Education: At least a Bachelor's degree in a related field or equivalent experience.
• Location-based hybrid policy: Staff expected in the office at least 25% of the time; some roles may require more.
• Visa sponsorship: Available with support from an immigration lawyer.

Benefits

• Competitive compensation and benefits.
• Optional equity donation matching.
• Generous vacation and parental leave.
• Flexible working hours.
• Collaborative office space in San Francisco headquarters.

How we're different

• Focus on big science with just a few large-scale research efforts.
• Emphasis on impact towards steerable, trustworthy AI.
• AI research treated as an empirical science akin to physics and biology.
• Extremely collaborative with frequent research discussions.
• Value communication skills.

Apply

We encourage candidates from diverse backgrounds and with different experience levels to apply. We value representation and believe people from underrepresented groups should not self-exclude.

For more details and to apply, visit the Anthropic careers page.