Research Product Manager - AI Systems

Research Product Manager - AI Systems (Structured Data, Evaluation & Learning Efficiency)About the RoleWe're hiring a Research Product Manager to define and build core systems that determine how AI models are evaluated, improved, and deployed on real-world data.You'll work on systems spanning:model evaluation and benchmarkingpost-training and feedback loopsstructured and relational data learningperformance, efficiency, and cost optimizationThis role sits at the intersection of ML infrastructure, research, and product. It is closest to roles like ML platform PM or AI infrastructure PM, but with deeper ownership of how systems are designed and how model performance translates into real-world outcomes.You'll partner closely with researchers and engineers to move ideas from experiments into production systems used at scale.The MissionAI today is no longer bottlenecked by model architecture alone.The real constraints are:how models are evaluatedhow they improve after traininghow they behave in real-world systemsGranica is building the systems that solve this.We are a research and systems company led by Prof. Andrea Montanari (Stanford), focused on:evaluation as a first-class systempost-training as a continuous learning loopefficient learning over real-world dataMost real-world data is structured and relational, yet modern AI systems remain poorly optimized to learn from it.Our thesis:AI advantage will come from how efficiently models learn from structured data-and how that translates into economic value.What You'll DoDefine and drive systems for model evaluation, benchmarking, and real-world performanceBuild product direction for post-training systems and feedback loops that continuously improve modelsDefine how models learn from large-scale structured and relational datasetsPartner with engineering to build systems that connect data platforms (warehouses, lakehouses) with ML systemsOwn how improvements move from research experiments into production systemsModel trade-offs across compute, data efficiency, performance, and costIdentify where system improvements drive measurable business impactSkills and QualificationsMinimum Qualifications5+ years of experience in product management, technical program management, or similar roles in AI, ML infrastructure, or data systemsStrong understanding of machine learning systems, including training, evaluation, and deploymentExperience working with large-scale data systems or distributed infrastructureAbility to reason about trade-offs across data, compute, performance, and costTrack record of driving complex technical systems from concept to productionPreferred QualificationsExperience with ML platforms, LLM systems, or AI infrastructureExperience with evaluation systems, observability, or model performance toolingFamiliarity with structured or relational data systems (e.g., warehouses, lakehouses)Background in engineering, applied research, or ML systems developmentExperience operating in research-driven or highly ambiguous environmentsIdeal BackgroundsML / AI infrastructure PMs (OpenAI, Google, Meta, Snowflake, Databricks, AWS, or similar)Product leaders in model systems, evaluation, or observabilityResearch engineers or applied scientists transitioning into productEngineers who have built ML or data systems and taken on product ownershipWhy This Role MattersMost AI systems are limited not by model capability, but by:weak evaluation systemsinefficient learning loopspoor utilization of structured datalack of connection between performance and real-world outcomesThis role defines how those constraints are solved in production systems.You won't be optimizing features-you'll be defining the systems that determine how models improve, how they are trusted, and how they deliver value.LogisticsLocation: Mountain View, CAWork model: On-site, five days per weekLevel: Senior / Staff / Principal (depending on experience)Compensation & BenefitsCompetitive salary, meaningful equity, and substantial bonus for top performersFlexible time off plus comprehensive health coverage for you and your familySupport for research, publication, and deep technical exploration