LILA has created the world's first Operating System for Science powered by Scientific Superintelligence™. Backed by General Catalyst.
About the role
We're building a talent-dense, high-agency AI safety team at Lila that will engage all core teams within the organization (science, model training, lab integration, etc.), to identify and mitigate risks from scientific superintelligence while retaining the core scientific discovery capabilities of the stack. The initial focus of this team will be to build and implement a bespoke safety strategy for Lila, tailored to its specific goals and deployment strategies. Found on 1752vc Careers, the job board for startup and VC roles.
What they're looking for
- Substantive experience assessing biological dual-use risks, with a strong understanding of relevant harmful applications, including pathogen- or toxin-related risks or other consequential biological misuse
- Prior experience applying biological expertise to AI safety through analysis informing threat models, evaluation or red-teaming work, or mitigation design
- Sound judgment about the relationship between computational predictions, biological function and experimental evidence, including uncertainty and the limits of your expertise
- Strong quantitative analysis and scientific programming skills, with the ability to develop computational approaches, run reproducible studies and critically investigate model outputs and biological data
- The ability to investigate unfamiliar questions, identify appropriate specialists and communicate defensible conclusions across scientific, engineering and policy teams
More about this role
We're building a talent-dense, high-agency AI safety team at Lila that will engage all core teams within the organization (science, model training, lab integration, etc.), to identify and mitigate risks from scientific superintelligence while retaining the core scientific discovery capabilities of the stack. The initial focus of this team will be to build and implement a bespoke safety strategy for Lila, tailored to its specific goals and deployment strategies. This will involve technical safety strategy development, broader ecosystem engagement, safety-focused evaluations, safety systems to mitigate risks, and a research agenda that explores longer-term needs such as oversight of superintelligent scientific systems.
You will conduct original computational biology research for AI safety and build an integrated understanding of biological risks. You will investigate how capabilities across large language models, specialized biological models, agents and automated laboratories combine to change what is biologically feasible. Our work spans protein and nucleic-acid design, cellular systems and biological delivery; we welcome other specialisms that bring relevant scientific depth and...
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