Research Product Manager, Post Training

Lila Sciences Lila Sciences · AI Frontier · Alewife, Cambridge, MA +1 · AI

Research Product Manager to set the vision for Lila’s foundational models, defining capabilities and performance that turn breakthrough research into real-world scientific impact. Owns the capability roadmap for core foundational model releases, synthesizing input from various stakeholders into a prioritized roadmap. Defines evaluation criteria, success metrics, and gating criteria for promoting models to production. Partners with research and model-training leads, and maintains documentation.

What you'd actually do

  1. Own the capability roadmap for Lila's core, foundational models: define and prioritize the specific capabilities each release should target, with an opinionated and defensible rationale for those choices.
  2. Translate input from domain/science teams, the product organization, and commercial stakeholders into concrete, measurable model requirements that researchers can build against.
  3. Perform ongoing analysis of competitive and frontier models - both general-purpose and scientific - turning benchmark results and capability gaps into roadmap decisions.
  4. Define the evaluation criteria and success metrics that determine whether a target capability has actually been achieved.
  5. Establish the gating criteria for promoting models to production.

Skills

Required

  • Bachelor's or Master's degree in Computer Science, Engineering, or a related field - or equivalent hands-on experience with AI/ML systems.
  • Proven product management experience for AI/ML products, ideally including ownership of a model, platform, or capability roadmap in a scientific domain.
  • A strong understanding of how foundational or large models are trained, evaluated, and released - with the ability to engage credibly with researchers and make sound prioritization calls.
  • A track record of translating stakeholder needs and competitive signal into clear, measurable requirements.
  • Experience defining release criteria and quality gates for a production system or model.
  • Excellent written and verbal communication, with a track record of driving cross-functional decisions.

Nice to have

  • Product management experience with foundation models, frontier models, or AI platforms.
  • Experience working at an AI-first research organization or in life sciences or materials science.
  • Familiarity with model evaluation methodologies, benchmarking, and evaluation infrastructure.
  • Comfort operating in fast-moving, ambiguous, early-stage research environments.

What the JD emphasized

  • Proven product management experience for AI/ML products, ideally including ownership of a model, platform, or capability roadmap in a scientific domain.
  • A strong understanding of how foundational or large models are trained, evaluated, and released
  • A track record of translating stakeholder needs and competitive signal into clear, measurable requirements.
  • Experience defining release criteria and quality gates for a production system or model.

Other signals

  • Product Manager for AI/ML products
  • ownership of a model, platform, or capability roadmap
  • defining release criteria and quality gates for a production system or model
  • synthesize signal from domain science teams, product, commercial opportunities, and the competitive model landscape into a clear, prioritized roadmap of model capabilities