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Generalist is building embodied foundation models and general intelligence for the physical world, with a focus on robot dexterity. The company was founded by researchers and engineers from OpenAI, Google DeepMind, and Boston Dynamics who have shipped breakthrough AI systems and next-generation robots.
You will own Generalist's external data supply chain end-to-end. Robot foundation models are constrained by data, and robotics training data must be deliberately manufactured through teleoperation, demonstration, filming, staging, and annotation in real environments. This role sits at the intersection of research requirements and operational execution.
Key responsibilities include: developing data supply strategy (buy vs. build decisions, vendor landscape mapping); sourcing and vetting new data partners through structured pilots; extracting actual requirements from ML and engineering leads and translating them into executable partner specifications; authoring unambiguous, partner-facing specs that non-ML operators can execute independently; structuring commercial terms, pricing, rate cards, and acceptance criteria; scaling individual partnerships into networks as capacity constraints emerge; maintaining operating cadence through trackers, weekly reviews, and forecasts against the research roadmap; closing feedback loops to inform future data cycles; and periodic travel to partner sites and collection operations.
Success requires deep vendor management experience, demonstrated ability to stand up new vendors from selection through ramp, skill translating technical requirements into clear instructions for non-technical partners, fluency with commercial mechanics and unit economics, exceptional written communication, comfort with incomplete requirements and mid-flight re-scoping, and consistent execution under pressure. The hardest part of the job is not the deal itself—it is the translation layer between researchers who speak in model language and partners who execute in operational terms.
