Anthropic

Research Engineer, Model Evaluations

Remote-Friendly (Travel-Required) | San Francisco, CA | New York City, NY

H1B sponsorship available$500k-$850kDetected 7 days ago

PythonDistributed SystemsMachine LearningData EngineeringData VisualizationLLMsStatisticsLogisticsResearchExperimental DesignLeadershipCommunication

About the role

Your work will turn ambiguous notions of "intelligence" into clear, defensible metrics that researchers, leadership, and the public can rely on.
The goal is to make Anthropic the leader in extremely well-characterized AI systems, with performance that is exhaustively measured and validated across the tasks that matter.
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

Design and run new evaluations of Claude's capabilities - reasoning, agentic behavior, knowledge, safety - 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
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
Experience building or operating distributed systems, data pipelines, or other infrastructure that needs to be reliable at scale
Comfort operating in an on-call or production-support capacity when training runs are live
Partner with a research team on a new capability area, helping them articulate what "good" looks like and translating that into measurable artifacts

Years of experience required will correlate with the internal job level requirements for the position
Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience
Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position

Hands-on experience using large language models such as Claude, including prompting, sampling, and scaffolding
Experience with observability, monitoring, or experiment-tracking systems
Experience with large-scale dataset sourcing, curation, and processing
Experience running or supporting ML training infrastructure
A bias toward picking up slack and operating flexibly across team boundaries
Enjoy pair programming - we love to pair
Representative projects
Diagnose a mid-training regression: an eval suite returns anomalous numbers, and you need to determine within hours whether it's the model, the harness, the data, or the infrastructure

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
Minimum education: Bachelor's degree or an equivalent combination of education, training, and/or experience

However, we aren't able to successfully sponsor visas for every role and every candidate.
But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.
We do sponsor visas!

This listing is sourced directly from Anthropic's careers page and normalized into a canonical job model.