Job description

Your Impact at LILA You'll own two connected but distinct areas. First, you'll decide which new scientific domain capabilities the Lila model should gain and how to build them — the right mix of reinforcement-learning environments and supervised fine-tuning (SFT) data — prioritized against our Target Product Profiles (TPPs) and customer needs. Second, you'll own the roadmap and end-to-end delivery of fine-tuned Lila model variants for priority platform and commercial use cases, including the training data, evals, and release criteria needed to ship them. These capability priorities also feed the AI Research team's core-model training cycle as a structured input, though that cycle itself sits outside this role's direct ownership. You'll sit within the Research Product Manager function and work side-by-side with AI Research, joining their sprint planning and standups, to ensure the right capabilities are built and upstream into the Lila foundation model. What You'll Be Building Own and maintain the prioritized backlog of training-capability packages (reinforcement-learning environments + SFT data), weighing Lila's TPPs, customer/commercial needs, and quarterly Lila model training needs Own the roadmap and delivery of fine-tuned Lila model variants for priority platform and commercial use cases: define the required training data, strategic data gaps, evals, and release criteria Coordinate the handoff of validated fine-tunes to the app and platform teams Serve as a structured input into the AI Research team's core-model training cadence, which sits outside this role's direct ownership Partner with AI Research (training-pipeline owners, evals, and data-mix leads) to translate prioritized capabilities into clear, well-specified requirements Represent customer- and commercial-driven capability requests, and translate them into concrete capability asks the research team can execute against Integrate into AI Research sprint planning and standups to track delivery and unblock cross-team dependencies Define and track release/acceptance criteria for new capabilities in partnership with the evals workstream, so shipped work can be validated before it informs fine-tuning or Lila model training What You'll Need to Succeed Experience as a Product Manager on ML/AI products, ideally with exposure to LLM training, fine-tuning, or RL-based capability development Experience owning delivery of a model or product variant for external or commercial customers, including defining data, evals, and release criteria Demonstrated ability to build and defend a prioritized backlog against competing scientific, research, and commercial demands Strong cross-functional operator, comfortable partnering closely with a research organization (joining sprint planning/standups, not just handing off requirements) Track record translating ambiguous or evolving priorities into a clear, sequenced set of deliverables Bonus Points For Familiarity with capability-based training approaches for LLMs (RL environments, SFT data generation, evals) Experience partnering with ML/AI research teams on eval design and release criteria Background in a scientific or technical domain relevant to Lila's mission 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 $204,000 — $310,000 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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Your Impact at LILA
What You'll Be Building
Own and maintain the prioritized backlog of training-capability packages (reinforcement-learning environments + SFT data), weighing Lila's TPPs, customer/commercial needs, and quarterly Lila model training needs
Own the roadmap and delivery of fine-tuned Lila model variants for priority platform and commercial use cases: define the required training data, strategic data gaps, evals, and release criteria
Coordinate the handoff of validated fine-tunes to the app and platform teams
Serve as a structured input into the AI Research team's core-model training cadence, which sits outside this role's direct ownership
Partner with AI Research (training-pipeline owners, evals, and data-mix leads) to translate prioritized capabilities into clear, well-specified requirements
Represent customer- and commercial-driven capability requests, and translate them into concrete capability asks the research team can execute against
Integrate into AI Research sprint planning and standups to track delivery and unblock cross-team dependencies
Define and track release/acceptance criteria for new capabilities in partnership with the evals workstream, so shipped work can be validated before it informs fine-tuning or Lila model training
What You'll Need to Succeed
Experience as a Product Manager on ML/AI products, ideally with exposure to LLM training, fine-tuning, or RL-based capability development
Experience owning delivery of a model or product variant for external or commercial customers, including defining data, evals, and release criteria
Demonstrated ability to build and defend a prioritized backlog against competing scientific, research, and commercial demands
Strong cross-functional operator, comfortable partnering closely with a research organization (joining sprint planning/standups, not just handing off requirements)
Track record translating ambiguous or evolving priorities into a clear, sequenced set of deliverables
Familiarity with capability-based training approaches for LLMs (RL environments, SFT data generation, evals)
Experience partnering with ML/AI research teams on eval design and release criteria
Background in a scientific or technical domain relevant to Lila's mission

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