Anthropic
Engineering Manager, Research Data Platform
$405K–$850K
San Francisco, CA +2 · Manager · Full-time · Posted Jul 6, 2026
- Location
- San Francisco, CA
New York City, NY
San Francisco, California, United States - Experience
- Years of experience correlate with internal job level requirements; no specific number stated.
- Education
- Bachelor’s degree or an equivalent combination of education, training, and/or experience; field relevant to the role as demonstrated through coursework, training, or professional experience.
- Visa sponsorship
- Visa sponsorship is available, but not for every role or candidate; if an offer is made, the company will make every reasonable effort to obtain a visa.
About the job
Set technical direction and build data platforms and canonical datasets that help AI researchers produce, find, query, and trust research data.
What you'll do
- Work with researchers to understand workflows and identify platform and dataset improvements.
- Design platform components and own core datasets, including pipelines, schemas, documentation, and guarantees.
- Lead cross-team projects, drive adoption of canonical datasets, and raise technical quality through reviews and mentorship.
What they ask for
- Experience building and operating data-intensive systems at scale, with strong data modeling and schema design.
- Experience setting technical direction for a team or owning architecture for a data platform used by other teams.
- Ability to lead through influence and work directly with internal users to discover needs and measure adoption.
Nice to have
- Experience with large-scale ETL and analytical storage, metrics or experiment-tracking systems, or dataset management and lineage tooling.
- Working knowledge of machine learning or experience working with an ML research lab.
Pay
$405,000 — $850,000 USD (base salary)
Tools
Spark, BigQuery, ClickHouse, DuckDB, Parquet
AI focus
Builds data infrastructure and canonical datasets supporting AI and machine learning research; deep ML expertise is not required.
Model-written summary · the original posting is authoritative