Lila Sciences is a startup building an AI platform that trains models on scientific literature and integrates laboratory validation to enable autonomous scientific discovery.
<p><strong>Your Impact at LILA</strong></p> <p>Lila’s foundational models are the engine behind scientific superintelligence. We are looking for a Research Product Manager to set the vision for what Lila’s foundational models can achieve next - defining the capabilities and performance that turn breakthrough research into real-world scientific impact.</p> <p>In this role, you will own the capability roadmap for Lila’s core foundational model releases. You will synthesize signal from domain science teams, product, commercial opportunities, and the competitive model landscape into a clear, prioritized roadmap of model capabilities. Sitting at the seam between research ambition and real-world impact, your work will help ensure every model we ship is aimed at the capabilities that matter most, and that research moves into production with confidence.</p> <p><strong>What You'll Be Building</strong></p> <ul> <li>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.</li> <li>Translate input from domain/science teams, the product organization, and commercial stakeholders into concrete, measurable model requirements that researchers can build against.</li> <li>Perform ongoing analysis of competitive and frontier models - both general-purpose and scientific - turning benchmark results and capability gaps into roadmap decisions.</li> <li>Define the evaluation criteria and success metrics that determine whether a target capability has actually been achieved.</li> <li>Establish the gating criteria for promoting models to production.</li> <li>Partner closely with research and model-training leads to sequence capability work realistically against compute, data, and timeline constraints.</li> <li>Maintain transparent documentation of capability targets, evaluation results, and release decisions so the reasoning behind every model is auditable and easy to revisit.</li> </ul> <p><strong>What You'll Need to Succeed</strong></p> <ul> <li>Bachelor's or Master's degree in Computer Science, Engineering, or a related field - or equivalent hands-on experience with AI/ML systems.</li> <li>Proven product management experience for AI/ML products, ideally including ownership of a model, platform, or capability roadmap in a scientific domain.</li> <li>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.</li> <li>A track record of translating stakeholder needs and competitive signal into clear, measurable requirements.</li> <li>Experience defining release criteria and quality gates for a production system or model.</li> <li>Excellent written and verbal communication, with a track record of driving cross-functional decisions.</li> </ul> <p><strong>Bonus Points For</strong></p> <ul> <li>Product management experience with foundation models, frontier models, or AI platforms.</li> <li>Experience working at an AI-first research organization or in life sciences or materials science.</li> <li>Familiarity with model evaluation methodologies, benchmarking, and evaluation infrastructure.</li> <li>Comfort operating in fast-moving, ambiguous, early-stage research environments.</li> <li> </li> </ul><div class="content-pay-transparency"><div class="pay-input"><div class="description"><p><strong>Compensation</strong></p> <p>We offer competitive base compensation with bonus potential and generous early-stage equity. Your final offer will reflect your background, expertise, and expected impact.</p> <p><strong>U.S. Benefits.</strong> 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.</p> <p><strong>International Benefits.</strong> 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.</p></div><div class="title">Expected Base Salary Range</div><div class="pay-range"><span>$204,000</span><span class="divider">—</span><span>$310,000 USD</span></div></div></div><div class="content-conclusion"><p><strong>About LILA</strong></p> <p>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.</p> <p>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.</p> <p>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.</p> <p><strong>We’re All In</strong></p> <p>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.</p> <p>Information you provide during your application process will be handled in accordance with our <a href="https://www.lila.ai/candidate-privacy-policy-notice">Candidate Privacy Policy</a>.</p> <p><strong>A Note