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

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates strong Python programming skills and experience in building reliable distributed systems and data pipelines. Capable of effectively communicating technical results to diverse audiences while ensuring model health and safety in AI evaluations.

Highest-signal resume keywords

Python ProgrammingDistributed SystemsData PipelinesClear CommunicationProduction Support

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Python ProgrammingDistributed SystemsData PipelinesModel EvaluationDebuggingExperimentationVisualizationsInfrastructure ReliabilityEvaluation ToolingBenchmarking

Soft Skills

Clear CommunicationTime ManagementCollaborationProblem-SolvingInterest in Societal Impact

Industry Keywords

AI SafetyModel Health MonitoringResearch InfrastructureProduction RL TrainingEvaluation Workflows

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