Product Intern, AI Science Factory at Lila Sciences in Cambridge, MA

Summary: Lila Sciences is the world’s first scientific superintelligence platform and autonomous lab for life, chemistry, and materials science. They are seeking a product intern to support the AI Science Factory product group in building analytical foundations, operational frameworks, and strategic materials for their platform. The role involves contributing to product strategy, maintaining databases, integrating software, conducting research, and developing materials for internal and external stakeholders. Responsibilities: - Contribute to capability roadmap development for the AISF platform, including workflow prioritization analysis, instrumentation gap assessments, and mapping of automation requirements across target therapeutic and materials programs - Maintain and extend Notion databases that connect capabilities, instruments, and opportunities to ongoing work — ensuring that the people executing on programs have current, structured information at hand - Work with the software product management team to integrate with Lila's laboratory automation software (LAS) platform, pulling information on instrument states, data production rates, and experimental throughput, and building automated dashboarding tools that surface operational visibility across the organization - Conduct research on laboratory automation, AI-driven experimentation platforms, and adjacent technologies to inform AISF capability expansion and competitive positioning - Develop workflow diagrams, capability matrices, and deliverables that articulate AISF technical capabilities, integration readiness, and value to both internal stakeholders and external partners Required Qualifications: - Currently pursuing or recently completed a graduate degree (MBA, MS, or PhD) or undergraduate degree (junior/senior) in engineering, science, business, or a related field - Strong analytical skills and comfort working with data — you can build a model, structure a database, or pull apart a dataset without hand-holding - Proficiency in at least one of: Python, SQL, or a comparable data analysis tool - Ability to synthesize information from multiple sources and teams into clear, structured outputs — written documents, diagrams, frameworks - Self-directed work style; you can take a loosely defined problem, figure out what needs to be true, and drive toward a deliverable - Fluency with AI and LLM tools as everyday working instruments — both for researching and exploring problem spaces (e.g., literature synthesis, landscape analysis, data interpretation) and for rapidly prototyping solutions through AI-assisted coding - Effective communication across technical and non-technical audiences Preferred Qualifications: - Familiarity with laboratory automation, scientific instrumentation, or experimental workflows - Experience with product management tools and methods — roadmapping, prioritization frameworks, stakeholder communication - Working knowledge of Notion, including database design and relational structures - Exposure to dashboarding or data visualization tools (e.g., Streamlit, Retool, Tableau, or custom solutions) - Background in life sciences, materials science, or chemistry — enough to navigate technical conversations without requiring constant translation - Comfort working in a fast-paced, ambiguous environment where scope and priorities shift Required Skills: Python, SQL, Data analysis Important Skills: Laboratory automation, Product management Nice-to-Have Skills: Self-directed work style, Fluency with AI tools