Design Lead for AI Systems

6 days ago

San Francisco, California, United States Anthropic Limited Full time

About the Role

We are seeking an experienced Research Engineer to join our Societal Impacts team at Anthropic Limited. As a key member of this team, you will design and build critical infrastructure that enables and accelerates foundational research into how our AI systems impact people and society.

The successful candidate will contribute directly to our research publications, policy campaigns, safety systems, and products. You will work closely with researchers, data scientists, policy experts, and other cross-functional partners to advance Anthropic's safety mission.

Key Responsibilities:

  • Design and Implement Scalable Infrastructure: Develop technical infrastructure that enables researchers to efficiently run experiments and evaluate AI systems.
  • Architect Systems for Uncertainty: Architect systems that can handle uncertain and changing requirements while maintaining high standards of reliability.
  • Lead Technical Design Discussions: Ensure our infrastructure can support both current needs and future research directions.
  • Partner with Researchers and Experts: Partner closely with researchers, data scientists, policy experts, and other cross-functional partners to advance Anthropic's safety mission.
  • Interface with Internal Tools: Interface with, and improve our internal technical infrastructure and tools.
  • Generate Insights: Generate net-new insights about the potential societal impact of systems being developed by Anthropic.
  • Inform Strategy and Policy: Translate insights to inform Anthropic strategy, research, and public policy.

You May Be a Good Fit If You:

  • Have 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.
  • Are comfortable making technical decisions with incomplete information while maintaining high engineering standards.
  • Have experience with distributed systems and can design for scale and reliability.
  • Have a track record of using technical infrastructure to interface effectively with machine learning models.
  • Have experience deriving insights from imperfect data streams.

Strong Candidates May Also Have Experience With:

  • Maintaining large, foundational infrastructure.
  • Building simple interfaces that allow non-technical collaborators to evaluate AI systems.
  • Working with and prioritizing requests from a wide variety of stakeholders, including research and product teams.
  • Scaling and optimizing the performance of tools.

Estimated Salary: $140,000 - $170,000 per year

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