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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 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 risk judgment.

Responsibilities

Formulate and pursue original computational biology research questions relevant to safety, developing computational approaches and designing and running studies that generate new evidence about biological capabilities, risks and safeguards.
Build and update an integrated picture of risks, examining how capabilities across LLMs, specialized biological models, agents and automated laboratories interact within scientific workflows and change practical constraints.
Combine research with literature, model assessments, experimental findings and expert input to judge biological feasibility, uncertainty and the significance of emerging capabilities for misuse.
Identify gaps in expertise, frame questions for external specialists and critically integrate their findings with support from the expert-program team.
Translate scientific risk judgments into dual-use policy boundaries, evaluation priorities and mitigation requirements that preserve beneficial biological research.
Work with threat modelers, automated-safety researchers, experimental scientists and mitigation engineers to design informative evaluations and red-teaming studies, test assumptions and assess safeguards.

Requirements

Deep expertise (a PhD, or comparable experience) in computational biology or a related quantitative biological discipline, with a record of original research from question formulation and computational study design through to defensible findings.
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.

Skills

Computational biology
AI safety
Biological risks
Large language models
Specialized biological models
Agents
Automated laboratories
Protein design
Nucleic-acid design
Cellular systems
Biological delivery
Quantitative analysis
Scientific programming
Threat modeling
Automated-safety research
Mitigation engineering
Biological dual-use risks
Pathogen-related risks
Toxin-related risks
Biological misuse
Model assessments
Experimental findings
Scientific risk judgments
Dual-use policy
Evaluation priorities
Mitigation requirements
Red-teaming studies

Work Type

Full-time

Experience Level

PhD or comparable experience

Education Level

Salary/Compensations

$268,000—$384,000 USD

Benefits

Medical coverage
Dental coverage
Vision coverage
Employer-paid life insurance
Employer-paid disability insurance
Flexible time off
Generous company wide holidays
Paid parental leave
Educational assistance program
Commuter benefits
Bike share memberships
Company subsidized lunch program

About the Company

Lila Sciences is building Scientific Superintelligence™ to solve humankind's greatest challenges.
We believe science is the most inspiring frontier for AI.
Rather than hard-coding expert knowledge into tools, LILA builds systems that can learn for themselves.
LILA combines advanced AI models with proprietary AI Science Factory™ instruments into an operating system for science that executes the entire scientific method autonomously, accelerating discovery at unprecedented speed, scale, and impact across medicine, materials, and energy.
Learn more at www.lila.ai.
Guided by our core values of truth, trust, curiosity, grit, and velocity, we move with startup speed while tackling problems of historic importance.

Equal Opportunity

Lila Sciences is committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status.