About the job
As a Research Engineer / Scientist on the Societal Impacts team, you'll design and build critical infrastructure that enables and accelerates foundational research into how our AI systems impact people and society. Your work will directly contribute to our research publications, policy campaigns, safety systems, and products.
Responsibilities
Design and implement scalable technical infrastructure that enables researchers to efficiently run experiments and evaluate AI systems.
Architect systems that can handle uncertain and changing requirements while maintaining high standards of reliability
Lead technical design discussions to ensure our infrastructure can support both current needs and future research directions
Partner closely with researchers, data scientists, policy experts, and other cross-functional partners to advance Anthropic’s safety mission
Interface with and improve our internal technical infrastructure and tools
Generate net-new insights about the potential societal impact of systems being developed by Anthropic
Ship changes that help improve our models and products based on the empirical research the Societal Impacts team is conducting
Qualifications
Minimum
Experience working ambiguous AI research projects
Experience building and maintaining production-grade internal tools or research infrastructure
Take pride in writing clean, well-documented code in Python that others can build upon
Comfortable making technical decisions with incomplete information while maintaining high engineering standards
Comfortable getting up-to-speed quickly on unfamiliar codebases, and can work well with other engineers with different backgrounds across the organization
Track record of using technical infrastructure to interface effectively with machine learning models
Have experience deriving insights from imperfect data streams
Experience building systems and products on top of LLMs
Preferred
Experience maintaining large, foundational infrastructure
Experience incubating and maturing tooling platforms used by a wide variety of stakeholders
Experience building simple interfaces that allow non-technical collaborators to evaluate AI systems
Experience working with and prioritizing requests from a wide variety of stakeholders, including research and product teams
Experience with distributed systems and designing for scale and reliability
Experience scaling and optimizing the performance of tools
Experience with product management and/or full-stack product engineering, with a track record of zero-to-one work in startup (or startup-like environments) and owning products end-to-end
Research relating to the societal impacts of technology