Software Engineer, Research Data Platform
Skills
About the role
This is a data-platform software engineering role building the tools Anthropic's researchers use to manage, query and analyze data behind model training and evaluation. It suits an engineer who likes working directly with technical users and building data products, and does not require prior ML experience. The role is based in San Francisco or New York City on a hybrid basis.
What you’ll do
- Build and operate data pipelines that move data out of training runs into queryable storage
- Design and build APIs, libraries and web interfaces for data management, exploration and analysis
- Develop dataset management, cataloging and provenance tooling
- Embed with research teams to identify tooling opportunities and ship solutions quickly
- Collaborate with adjacent teams to build on existing systems rather than reinvent them
What they’re looking for
- Significant software engineering experience, particularly with data-intensive applications or internal tooling
- Enjoys working directly with users and shipping things that get adopted
- Results-oriented with a bias toward flexibility and impact
- Willingness to pick up work outside the immediate job description
- Interest in learning about machine learning research
- Cares about the societal impact of the work
Nice to have
- Large-scale ETL, columnar storage and query engines such as Spark, BigQuery, DuckDB or Parquet
- High-volume time series data ingestion and querying
- Data cataloging, lineage or metadata management systems
- ML experiment tracking or metrics platforms
- Experience partnering closely with quantitative users, e.g. research labs or trading firms
- Complex data visualization and full-stack web development
What’s on offer
- USD 320,000-405,000
Questions about this role
Is this role remote?
No, it is hybrid, based in San Francisco or New York City.
How much does it pay?
USD 320,000-405,000.
Do I need ML experience?
No, prior ML or AI training experience is not required.
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