Your Impact at LILAWe are looking for a Program Lead to own strategy and execution for Lila's Materials Science AISF program. This role defines how and when the program delivers against Product, Science, and AI priorities, then turns that strategy into clear charters, budgets, timelines, and execution plans.
Materials Science AISFs span vacuum synthesis, characterization, electrochemistry, nanoporous materials, and physics. The Program Lead will connect deep domain expertise, platform strategy, and cross-functional execution to expand the experimental systems that help AI learn materials science at scale.
This role reports to John Gregoire and partners closely with Product, AISF Engineering, Materials Experiment, Scientific Programs, and technical leadership. Success requires clear strategy, decisive execution, and the ability to align teams around complex, high-impact platform priorities.
What You'll Be Building- Own the Materials Science AISF program strategy, charter, budget, timeline, and success criteria.
- Translate Product, Science, and AI priorities into executable program plans.
- Build the roadmap for expanding Materials Science AISF capabilities across synthesis, characterization, and closed-loop AI guidance.
- Evaluate proof-of-concept results from Scientific Programs and design pathways for platform integration.
- Form, align, and advise cross-functional project teams executing the Materials Science AISF strategy.
- Resolve resourcing, prioritization, and execution risks in partnership with Product and portfolio leads.
- Represent Materials Science AISF strategy, status, risks, and decisions in technical leadership reviews.
What You'll Need to Succeed- PhD or equivalent experience in materials science, condensed matter physics, chemistry, or a closely related field, with industry research experience.
- Track record leading complex, multidisciplinary experimental programs.
- Familiarity with Materials Science AISF domains such as vacuum synthesis, characterization, electrochemistry, or nanoporous systems.
- Experience defining and managing technical roadmaps with real resource, budget, and timeline constraints.
- Strong written and verbal communication, with the ability to translate technical depth into strategic clarity.
- Experience leading through influence across matrixed, cross-functional teams.
Bonus Points For- Experience with automated or high-throughput experimental platforms, robotics, or lab automation.
- Familiarity with AI/ML-driven experimental design, Bayesian optimization, or closed-loop materials discovery.
- Exposure to atomistic simulation methods and their relationship to experimental programs.
- Experience in a fast-paced research environment such as a national lab, advanced materials startup, or deep-tech company.
- Experience working across shared resources and multiple concurrent programs.
CompensationWe 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
$320,000-$380,000 USD
