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Anthropic

Research Engineer, Model Evaluations

Anthropic

Research Engineer building evaluations for Claude's capabilities at Anthropic. Collaborating with researchers and utilizing Python for scalable evaluations.

Posted 7/9/2026full-timeSan Francisco • California, New York • 🇺🇸 United StatesMid-LevelSenior💰 $500,000 - $850,000 per yearWebsite

Tech Stack

Tools & technologies
Distributed SystemsPython

About the role

Key responsibilities & impact
  • Design and run new evaluations of Claude's capabilities — reasoning, agentic behavior, knowledge, safety properties — and produce visualizations that make the results legible to researchers and decision-makers
  • Build and harden the distributed eval execution platform so hundreds of evals run reliably against checkpoints throughout production RL training runs
  • Own the dashboards researchers and leadership use to monitor model health during training, improving signal-to-noise, reducing latency, and making regressions impossible to miss
  • Debug anomalous eval results mid-training-run, determine whether the cause is a model change or an infrastructure issue, and communicate the answer clearly under time pressure
  • Improve the tooling, libraries, and workflows researchers use to implement and iterate on evaluations
  • Partner with research teams across the full lifecycle of a new capability — from defining what to measure to interpreting results as training progresses
  • Run experiments to characterize how prompting, sampling, and scaffolding choices affect results on internal and industry benchmarks
  • Communicate evaluations and their results to internal stakeholders and, where appropriate, external audiences

Requirements

What you’ll need
  • Strong Python programming skills, including production or research infrastructure
  • Experience building or operating distributed systems, data pipelines, or other infrastructure that needs to be reliable at scale
  • Clear written and verbal communication, especially when explaining technical results to non-specialists
  • Comfort operating in an on-call or production-support capacity when training runs are live
  • Care about the societal impacts of your work and an interest in steering powerful AI to be safe and beneficial
  • Bachelor’s degree or an equivalent combination of education, training, and/or experience

Benefits

Comp & perks
  • Flexible working hours
  • Generous vacation and parental leave
  • Competitive compensation and benefits
  • Optional equity donation matching
  • Lovely office space to collaborate with colleagues

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools
Python ProgrammingDistributed SystemsData PipelinesModel EvaluationDebuggingExperimentationVisualizationsInfrastructure ReliabilityEvaluation ToolingBenchmarking
Soft Skills
Clear CommunicationTime ManagementCollaborationProblem-SolvingInterest in Societal Impact