Research Scientist I/II, AI Safety, Biological/ Physical Sciences

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 prepare for risks from scientific superintelligence. 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, as well as developing technical collateral including risk‑ and capability‑focused evaluations and safeguards. What You’ll Be Building Design and build capability evaluations to test for scientific risks (both known but especially novel) from cutting edge scientific models integrated with automated physical labs, across biological / physical sciences. Coordinate and lead threat modelling exercises with internal and external scientific experts, including monitoring for emerging technologies and use‑cases. Develop and curate high-quality training and test data for evals and safety systems. Evaluate risks from Lila’s capabilities, including through interactions with the wider ecosystem of capabilities (e.g. general‑purpose frontier models as well as narrow scientific tools) Contributing to broader, high‑quality research efforts - as and when needed - for scientific capability evaluation and restriction. Contribute to external communications on Lila’s safety efforts. What You’ll Need to Succeed A PhD in either a biological sciences domain (e.g., molecular biology, virology, computational biology or related fields) or a physical sciences domain (materials sciences, physics, chemistry, chemical or nuclear engineering, or related fields), or other related experience. Experience in scientific computing, across either biological or physical sciences. Familiarity with dual‑use research and dissemination concerns, across the relevant safety / regulatory / governance frameworks (e.g. export control frameworks, biological and chemical‑related conventions and controls). Ability to communicate complex technical concepts and concerns to non‑expert audiences effectively. Demonstrated ability to lead teams of internal and external collaborators in buildout of Lila’s point‑of‑view on biological / physical risks. Demonstrated ability to deal with cross‑functional stakeholders (science, AI, product, policy) in a complex environment. Bonus Points For Experience in developing or applying ML to biological or physical sciences. Experience in building evaluations, or conducting red‑teaming exercises, across scientific risks for frontier models / narrow scientific tools. Location This position may be based in any of Lila’s offices, including Cambridge (MA), San Francisco (CA), or London (UK). Compensation For US‑based candidates (Cambridge or San Francisco), we expect the base salary for this role to fall between $176,000–$304,000 USD per year, along with bonus potential and generous early equity. The final offer will reflect your unique background, expertise, and impact. For UK‑based candidates, compensation will be determined separately and will be aligned with local market benchmarks and internal leveling. 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. Equal Employment 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. #J-18808-Ljbffr Dormont Manufacturing Co