SlipstreamJobs tracks this role from the company's public career site. Apply directly on the employer's site.
Salary: USD 204,000 - 310,000 / annual
Lila Sciences is seeking a Research Product Manager to own the strategy and delivery of fine-tuned model variants and new scientific domain capabilities for their AI platform. You will have dual ownership: (1) deciding which new scientific capabilities the Lila model should develop, determining the optimal mix of reinforcement-learning environments and supervised fine-tuning data, and prioritizing against Target Product Profiles and customer needs; and (2) owning the roadmap and end-to-end delivery of fine-tuned model variants for priority platform and commercial use cases, including training data, evaluation frameworks, and release criteria.
Key responsibilities include maintaining a prioritized backlog of training-capability packages, defining required training data and strategic data gaps, coordinating handoffs to app and platform teams, and serving as a structured input into the AI Research team's core-model training cycle. You will partner closely with AI Research teams on training pipelines, evaluation design, and data-mix strategy, integrating into their sprint planning and standups to track delivery and unblock dependencies. You'll translate customer and commercial capability requests into concrete, well-specified requirements that research teams can execute against, and define acceptance criteria for new capabilities in partnership with the evaluation workstream.
Required experience includes product management on ML/AI products with exposure to LLM training, fine-tuning, or RL-based capability development; demonstrated ability to own delivery of model or product variants for external or commercial customers; and a track record building and defending prioritized backlogs against competing scientific, research, and commercial demands. You should be a strong cross-functional operator comfortable partnering closely with research organizations and translating ambiguous priorities into clear, sequenced deliverables. Bonus qualifications include familiarity with capability-based training approaches for LLMs, experience with ML/AI research team collaboration on eval design, and background in a scientific or technical domain relevant to the company's mission.
