About the role
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
