Anthropic is recruiting an Engineering Manager for its Research Data Platform team. The role involves leading technical direction, designing platform components, owning end‑to‑end data pipelines, and driving convergence toward canonical datasets that researchers rely on. The manager will work closely with researchers and engineers, shaping solutions that enable efficient data production, discovery, and trust. The position supports hybrid work with on‑site presence in San Francisco or New York.
Engineering Manager, Research Data Platform at Anthropic
Hybrid - San Francisco, CA | New York City, NY
More jobs at AnthropicSalary
USD 405,000 - 850,000
Requirements
Skills
- Built and operated data-intensive systems at scale — pipelines, storage layers, query systems — with strong instincts for data modeling and schema design
- Set technical direction for a team, or owned the architecture of a data platform that other teams build on
- Treat internal users as customers: discovery work, iterate with users, measure success by adoption rather than shipping
- Understand that researchers aren’t typical internal customers — work is exploratory, workflows differ, and requirements are discovered through experiments
- Build for stable interfaces and trustworthy data while use cases change
- Lead through influence — align engineers and stakeholders without relying on formal authority
- Results-oriented and pragmatic, willing to do unglamorous work when it’s highest-leverage
- Excited about learning fundamentals of machine learning research (deep ML expertise not required)
- Care about societal impacts of your work
- Experience with large-scale ETL and columnar or analytical storage (e.g., Spark, BigQuery, ClickHouse, DuckDB, Parquet)
- Experience with metrics or experiment-tracking systems, or high-volume time-series data
- Experience with dataset management, cataloging, or lineage tooling
- Built developer tooling or internal data platforms for demanding technical users — including in domains like quantitative trading
- Working knowledge of machine learning
- Worked in or closely with an ML research lab
- Interest in or experience with people management and growing engineers
Responsibilities
- Work directly with researchers and the engineers supporting them to understand their workflows, identify the highest-leverage opportunities, and shape what the team builds next
- Set the technical direction for the team across our platform and our datasets
- Design and build platform components that other teams plug into — libraries, services, and interfaces such as the metrics library used by training frameworks
- Own core datasets end to end: the pipelines that produce them, the schemas that define them, and the documentation and guarantees that make researchers trust them
- Drive convergence toward canonical datasets — including the core data model for RL transcripts — that research teams standardize on
- Lead complex, multi-quarter projects that span several systems and teams, staying hands‑on in the code
- Raise the team's technical bar through design reviews, mentorship, and the quality of your own work
Technologies
Data pipelinesData storage layersQuery systemsMetrics librarySparkBigQueryClickHouseDuckDBParquetMetrics or experiment‑tracking systemsTime‑series dataDataset managementCatalogingLineage toolingMachine learningML research tools
See if your resume is ready for this job
See how our AI can optimize your resume and improve your chances for this role.