Software Engineer, Research Data Platform

Software Engineer, Research Data Platform About the Role The Research Data Platform team builds the tools that Anthropic's researchers use every day to manage, query, and analyze the data that goes into training and evaluating frontier models. We power internal applications researchers rely on to monitor RL runs, explore finetuning datasets, and understand experiments. We look for engineers who build data products—pipelines that move data from training runs into queryable storage, and APIs, libraries, and services researchers use to manage and explore it. This role sits closer to the research workflow than a typical data infrastructure position: you embed with research teams, build ML‑specific tooling alongside them, and leverage existing pipeline infrastructure rather than reinventing it. Responsibilities Build and operate data pipelines that extract data from research training runs and land it in storage systems that are easy and fast to query. Work closely with researchers to design and build APIs, libraries, and web interfaces that support data management, exploration, and analysis. Develop dataset management, data cataloging, and provenance tooling that researchers use in their day‑to‑day work. Embed with research teams to understand their workflows, identify high‑leverage tooling opportunities, and ship solutions quickly. Collaborate with adjacent teams to build on existing systems rather than reinventing them. Qualifications Significant software engineering experience, especially building data‑intensive applications or internal tooling. Enjoy working directly with users, gathering requirements iteratively, and shipping adopted solutions. Results‑oriented, with a bias toward flexibility and impact. Pick up slack, even if it goes outside your job description. Want to learn more about machine learning research. Care about the societal impacts of your work. Preferred Experience Large‑scale ETL, columnar storage formats, and query engines (e.g., Spark, BigQuery, DuckDB, Parquet). High‑volume time‑series data ingestion, storage, and efficient querying. Data cataloging, lineage, or metadata management systems. ML experiment tracking or metrics platforms. Experience partnering closely with quantitative users in research labs, trading firms, or analytics startups. Complex data visualization and full‑stack web application development. Compensation Annual range: $320,000 – $405,000 USD Logistics Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience. Required field of study: Relevant to the role, demonstrated through coursework, training, or professional experience. Minimum years of experience: Correlates with the internal job level requirements. Location‑based hybrid policy: Expect all staff to be in an office at least 25% of the time. Visa sponsorship: We sponsor visas when available and solidify arrangements through an immigration lawyer. Equal Employment Opportunity: As set forth in Anthropic’s Equal Employment Opportunity policy, we do not discriminate on the basis of any protected group status under any applicable law. #J-18808-Ljbffr