Source-listed Job

Senior / Principal Computational Biologist, AI Safety

Your Impact at LILA

Job Source description available
Lila Sciences Cambridge, MA, Alewife, Cambridge, MA, Europe, San Francisco, CA Source published Oct 21, 2026 Source retrieved Oct 21, 2026
Source: Lilasciences (greenhouse) · A retrieval date records when our system last obtained the source record. It does not guarantee the vacancy is still open or that every detail has been independently checked.
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Overview

Your Impact at LILA

Full job description

Your Impact at LILA 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 risk judgment. What You'll Be Building 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 your 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. What You'll Need to Succeed 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. Bonus Points For Experience connecting biological modeling or design to experimental validation, including workflows combining LLMs, specialized models, agents or laboratory automation. Experience commissioning specialist research or coordinating external scientific collaborators. Compensation We offer competitive base compensation with bonus potential and generous early-stage equity. Your final offer will reflect your background, expertise, and expected impact. U.S. Benefits. Full-time U.S. employees receive a comprehensive benefits program including medical, dental, and vision coverage; employer-paid life and disability insurance; flexible time off with generous company wide holidays; paid parental leave; an educational assistance program; commuter benefits, including bike share memberships for office based employees; and a company subsidized lunch program. International Benefits. Full-time employees outside the U.S. receive a comprehensive benefits program tailored to their region. USD salary ranges apply only to U.S.-based positions; international salaries are set to local market. Expected Base Salary Range $268,000 — $384,000 USD About LILA 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. If this sounds like an environment you'd love to work in, even if you don't meet every qualification listed above, we encourage you to apply. We’re All In 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. Information you provide during your application process will be handled in accordance with our Candidate Privacy Policy . A Note to Agencies Lila Sciences does not accept unsolicited resumes from any source other than candidates. The submission of unsolicited resumes by recruitment or staffing agencies to Lila Sciences or its employees is strictly prohibited unless contacted directly by Lila Science’s internal Talent Acquisition team. Any resume submitted by an agency in the absence of a signed agreement will automatically become the property of Lila Sciences, and Lila Sciences will not owe any referral or other fees with respect thereto.

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