The Research Engineer on the Economic Research Data Platform team at Anthropic will design, build, and maintain critical infrastructure that powers the company’s research into AI’s economic impact. The role involves building data pipelines, developing APIs and libraries for researchers and the public, and collaborating with cross‑functional teams such as Data Science, Analytics, Societal Impacts, and Public Policy to ensure reliable, privacy‑preserving data systems.
Research Engineer, Economic Research Data Platform na Anthropic
Presencial - San Francisco, CA, United States
Ver mais vagas na AnthropicSalary
USD 320,000 - 405,000
Requirements
Skills
- Significant experience building data-intensive applications, pipelines, or internal tooling in production
- Experience with cloud infrastructure platforms such as AWS or GCP, and take pride in writing clean, well-documented code in Python that others can build upon
- Intuition for analytics workflows and empathy for how researchers and data scientists work
- Comfortable making technical decisions with incomplete information while keeping engineering standards high
- Full-stack mindset
- Strong communication skills to collaborate effectively with economists, researchers, and cross-functional partners who may have varying levels of technical expertise
- Care about the societal impacts of your work, and are interested in AI's economic implications
- Bachelor’s degree or an equivalent combination of education, training, and/or experience
- Experience with modern data transformation, orchestration, and query frameworks
- Building systems and products on top of LLMs
- Privacy-preserving data systems, or data governance and lineage tooling
- Building and operating web services and the infrastructure underneath them
- Full-stack development or complex data visualization
- Background in econometrics, statistics, or quantitative social science
- Working in environments where engineers partner closely with quantitative users — research labs, trading firms, analytics companies
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 — for understanding how Claude is used and the impact it's having on the economy
- Build self-serve workflows to ingest and integrate external data sources so they're 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
AWSGCPPythonML pipelinesData pipelinesPrivacy-preserving data systemsLLMs
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