Research Engineer on the Economic Research Data Platform team, designing, building, and maintaining critical infrastructure that powers Anthropic’s research on AI’s economic impact. The role involves working with data systems across Anthropic, including research tools for privacy‑preserving analysis, building scalable systems to monitor AI usage patterns, and directly measuring the impact of AI adoption on real‑world outcomes.
Research Engineer, Economic Research Data Platform at Anthropic
On-site - San Francisco, CA
More jobs at AnthropicSalary
USD 235,000 - 285,000
Requirements
Skills
- Significant experience building data-intensive applications, pipelines, or internal tooling in production
- Experience with cloud infrastructure platforms such as AWS or GCP
- Proficiency in Python with clean, well‑documented code
- Intuition for analytics workflows and empathy for how researchers and data scientists work
- Comfort making technical decisions with incomplete information while maintaining high engineering standards
- Full‑stack mindset, willing to solve end‑to‑end problems
- Strong communication skills to collaborate with economists, researchers, and cross‑functional partners
- Interest in societal impacts of AI and AI’s economic implications
- Experience with modern data transformation, orchestration, and query frameworks (bonus)
- Experience building systems and products on top of LLMs (bonus)
- Experience with privacy‑preserving data systems or data governance and lineage tooling (bonus)
- Experience building and operating web services and their underlying infrastructure (bonus)
- Full‑stack development or complex data visualization experience (bonus)
- Background in econometrics, statistics, or quantitative social science (bonus)
- Experience in environments where engineers partner closely with quantitative users such as research labs, trading firms, analytics companies (bonus)
Responsibilities
- Build and operate the data pipelines that turn raw usage data into clean, reusable, privacy‑preserving datasets
- Design new systems—including developing classifiers, training probes on model internals, and building the ML pipelines behind them—to understand how Claude is used and the impact it is having on the economy
- Build self‑serve workflows to ingest and integrate external data sources so they are interoperable with internal datasets
- Develop the APIs, libraries, and interfaces that serve data to researchers and the public
- Partner closely with researchers, data scientists, policy experts, and other cross‑functional partners to advance Anthropic’s safety mission
- Contribute to the team roadmap, documentation, and practices that enable self‑serve data access while maintaining safety and governance standards
- Ensure data reliability, integrity, and privacy compliance across all economic research data infrastructure
Technologies
Data pipelinesPrivacy‑preserving data analysisClassifiersModel internals probesMachine learning pipelinesExternal data source integrationAPIs and librariesAWSGCPPythonModern data transformation frameworksOrchestration toolsQuery frameworksLarge Language Models (LLMs)Privacy‑preserving data systemsData governance and lineage toolingWeb servicesFull‑stack developmentData visualization
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