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

• Set the build and research strategy for Lila’s safety approach to biological / physical risks.
• 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.
• Demonstrated ability to set research directions for open problems in dual-use risks in the biological / physical sciences.
• 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.

• This position may be based in any of Lila's offices, including Cambridge (MA), San Francisco (CA), or London (UK).

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.

• This position may be based in any of Lila's offices, including Cambridge (MA), San Francisco (CA), or London (UK).

• 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.

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

• Evaluations to test for scientific risks (both known but especially novel) from cutting edge scientific models integrated with automated physical labs
• Initial proof-of-concept safeguards, such as ML models to detect and block unsafe behavior from scientific AI models, as well as from physical lab outputs.
• Understanding of a range of model capabilities, across primarily scientific but also non-scientific domains (e.g. persuasion, deception) to inform Lila's broader safety strategy.
• Broader, high-quality research efforts - as and when needed - for scientific capability evaluation and restriction.

What You’ll Need to Succeed

• Bachelor's degree in a technical field (e.g., computer science, engineering, machine learning, mathematics, physics, statistics), or related experience.
• Strong programming skills in Python, and experience with ML frameworks (including, for instance, Inspect) for large-scale evaluation and scaffolded testing.
• Experience in building evaluations, or conducting red-teaming exercises, for CBRN / cyber risks (or for frontier model capabilities more generally, including both unsafe and benign capabilities)
• Experience in designing and/or implementing (directly or through consultation) AI safety frameworks for frontier AI companies.
• Ability to communicate complex technical concepts and concerns to non-expert audiences effectively.

Bonus Points For

• Masters or PhD in a field relevant to safety evaluations of AI models in scientific domains, or a technical field.
• Publications in AI safety / evaluations / model behaviour in top ML / AI conferences (NeurIPS, ICML, ICLR, ACL) or model release system cards.
• Experience researching risks from novel science (e.g. biosecurity, computational biology, etc.) or working with narrow scientific tools (e.g. large scale foundation models for science).

• This position may be based in any of Lila's offices, including Cambridge (MA), San Francisco (CA), or London (UK).