Private, domain-specific benchmarks in legal, tax, and finance. Backed by a16z and Pear VC.
About the role
We are looking for an exceptional researcher to design and build the next generation of AI benchmarks for catching misaligned behavior in frontier models and agents, e.g., reward hacking, scheming, deception, loss of control, multi-agent safety, etc. You will create high-impact, challenging evaluations that push the boundaries of what we can measure in foundation models. This role is ideal for someone with deep research expertise who wants to see their work directly influence how the world evaluates AI systems. Found on 1752vc Careers, the job board for startup and VC roles.
What they're looking for
- Deep ML/AI background: An understanding of neural networks and the fundamentals behind the model training process
- Strong engineering: Excellent coding skills and the ability to design and build complex evaluation environments yourself, mostly in Python
- Communication : Ability to clearly communicate complex research ideas to both technical and non-technical audiences
- Location: We are an in-person team in San Francisco and will support relocation or transportation as needed
- Learning velocity: The role encompasses a wide variety of tasks. Rather than expecting you to be an expert on Day 1, we are looking for someone who can learn new skills and technologies quickly
- Ownership : Working in a small, talent-dense team, we expect everyone to show initiative to build where it's needed, not where it's asked. We strive for autonomy over consensus
More about this role
Note: This is an application for those specifically interested in building benchmarks to assess AI safety. If you are interested in other domains, please see our general research posting . We encourage you to only apply to one research posting.
We are looking for an exceptional researcher to design and build the next generation of AI benchmarks for catching misaligned behavior in frontier models and agents, e.g., reward hacking, scheming, deception, loss of control, multi-agent safety, etc. You will create high-impact, challenging evaluations that push the boundaries of what we can measure in foundation models. This role is ideal for someone with deep research expertise who wants to see their work directly influence how the world evaluates AI systems.
You will lead the design and development of novel benchmarks and infrastructure that help assess misalignment risks in LLMs. Our benchmarks shape how foundation models are developed and generative AI applications are built. We work with every major foundation model lab - along with leading financial institutions and the application-layer companies pushing the frontier forward. Our work has been featured by the Wall Street Journal,...
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