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Scientist​/Sr. Scientist, AI Safety

Job in Cambridge, Middlesex County, Massachusetts, 02140, USA
Listing for: Dormont Manufacturing Co
Full Time position
Listed on 2026-05-30
Job specializations:
  • IT/Tech
    AI Engineer, Data Scientist, Machine Learning/ ML Engineer
Salary/Wage Range or Industry Benchmark: 228000 - 358000 USD Yearly USD 228000.00 358000.00 YEAR
Job Description & How to Apply Below

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

Expected Base Salary Range

$228,000—$358,000 USD

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

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

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