About 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.

Note: We are not actively hiring for this team at the time, but we are keeping this up to collect expressions of interest. Once we are hiring again, we may reach out to you if we see a mutual fit.

About the role

As a Research Engineer on the Model Evaluations team, you'll lead the design and implementation of Anthropic's evaluation platforma critical system that shapes how we understand, measure, and improve our models' capabilities and safety. You'll work at the intersection of research and engineering to develop and implement model evaluations that give us insight into emerging capabilities and build robust evaluation infrastructure that directly influences our training decisions and model development roadmap. Your work will be essential to Anthropic's mission of building safe, beneficial AI systems. You'll collaborate closely with training teams, alignment researchers, and safety teams to ensure our models meet the highest standards before deployment. This is a technical leadership role where you'll drive both the strategic vision and hands-on implementation of our evaluation systems.

Responsibilities

• Design novel evaluation methodologies to assess model capabilities across diverse domains including reasoning, safety, helpfulness, and harmlessness
• Lead the design and architecture of Anthropic's evaluation platform, ensuring it scales with our rapidly evolving model capabilities and research needs
• Implement and maintain high-throughput evaluation pipelines that run during production training, providing real-time insights to guide training decisions
• Analyze evaluation results to identify patterns, failure modes, and opportunities for model improvement, translating complex findings into actionable insights
• Partner with research teams to develop domain-specific evaluations that probe for emerging capabilities and potential risks
• Build infrastructure to enable rapid iteration on evaluation design, supporting both automated and human-in-the-loop assessment approaches
• Establish best practices and standards for evaluation development across the organization
• Mentor team members and contribute to the growth of evaluation expertise at Anthropic
• Coordinate evaluation efforts during critical training runs, ensuring comprehensive coverage and timely results
• Contribute to research publications and external communications about evaluation methodologies and findings

You may be a good fit if you

• Have experience designing and implementing evaluation systems for machine learning models, particularly large language models
• Have demonstrated technical leadership experience, either formally or through leading complex technical projects
• Are skilled at both systems engineering and experimental design, comfortable building infrastructure while maintaining scientific rigor
• Have strong programming skills in Python and experience with distributed computing frameworks
• Can translate between research needs and engineering constraints, finding pragmatic solutions to complex problems
• Are results-oriented and thrive in fast-paced environments where priorities can shift based on research findings
• Enjoy collaborative work and can effectively communicate technical concepts to diverse stakeholders
• Care deeply about AI safety and the societal impacts of the systems we build
• Have experience with statistical analysis and can draw meaningful conclusions from large-scale experimental data