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Embodied AI Simulation Product Manager

Shanghai

Responsibilities

  1. Own product planning, industry solution design, and ecosystem building for the company core physical AI simulation platform (ORCA). This role requires a deep understanding of the embodied AI simulation technology stack, the ability to convert complex technical capabilities into implementable industry product solutions, and driving commercial adoption in key sectors such as power and industrial manufacturing.
  2. Product planning and definition: own requirements planning for the embodied AI simulation platform (ORCA), covering core modules such as synthetic data generation, multi-physics simulation, and RL training closed loops; define product feature boundaries, performance metrics, and UX standards, and deliver high-quality PRDs, product white papers, and technical documentation
  3. Industry solution design: design end-to-end simulation training solutions for industries such as power and industrial manufacturing; conduct requirements research with industry customers, convert business pain points into product requirements, and deliver industry solution PPTs and technical proposals to support business development and ecosystem cooperation
  4. Technical ecosystem analysis: continuously track technology trends in embodied AI simulation, including frontier directions such as VLA models and generative simulation, and conduct technical ecosystem analysis
  5. Cross-team collaboration and communication: serve as the core bridge between technical and business teams, coordinating R&D, algorithm, sales, and marketing resources, and deliver product presentations and technical demos to customer executives and at industry forums (e.g., WAIC)

Requirements

  1. Technical background: bachelor degree or above with 3+ years of work experience (requirements may be relaxed for outstanding candidates); deep understanding of the embodied AI simulation technology stack; familiar with at least one of Isaac Sim or MuJoCo, and with robot body structures including kinematics, dynamics, and sensor modeling
  2. Algorithm awareness: systematic understanding of reinforcement learning (RL), imitation learning (IL), VLA models, and world models; aware of the applicable scenarios and trade-offs of RL frameworks such as Stable Baselines3, RSL, RLlib, and SKRL
  3. Product capability: 0-to-1 product definition experience, able to independently write PRDs, design prototypes, break down user stories, and plan iterations
  4. Documentation and expression: outstanding PPT skills with a tech-business aesthetic, strong information density control and data visualization ability; able to write high-quality technical documentation, white papers, and industry analysis reports with precise expression and self-consistent logic
  5. Communication and collaboration: excellent cross-team and customer communication skills, able to convert complex technical concepts into customer-understandable business value

Bonus Points

  • Industrial manufacturing experience: familiarity with scenarios such as smart manufacturing, flexible production lines, and digital twin factories, with simulation training project experience for industrial robots (collaborative robots, AGV/AMR)
  • Embodied AI ecosystem resources: cooperation resources with robot body manufacturers, model training vendors, or university research institutions