What we’re doing isn’t easy, but nothing worth doing ever is. We envision a future powered by robots that work seamlessly with human teams. We build artificial intelligence that enables service robots to collaborate with people and adapt to dynamic human environments. Join our mission-driven, venture-backed team as we build out current and future generations of humanoid robots.As the Tech Lead/Manager, Embodied AI, you’ll lead a mission-critical team: building the AI that lives on the robot. You’ll own the robotics software stack (core robotics behaviors, and robotics platform, middleware, etc.) and the multimodal end to end models that enable perception, navigation, manipulation and adaptive collaboration. This is hands-on leadership in a startup setting: you’ll lead, build, mentor, and code as well as ensure the end-to-end system works in the real world.Lead and grow an embodied-AI team that owns perception, planning, navigation, manipulation, and multimodal ML models, all running on edge platformsDefine the strategic technical roadmap for the robotics platform and embodied-AI capabilities—from foundational models to real-time onboard inference and control.Architect and guide development of large multimodal ML models—vision, language, tactile—that drive physical robot behaviors, potentially leveraging foundation model approaches.Oversee integration between edge AI, firmware, OS, hardware, and cloud services for deployment, monitoring, and continuous improvement.Provide hands-on leadership: mentor engineers, review code and models, and contribute directly to critical system components.Ensure AI and robotics systems meet safety, robustness, and regulatory requirements; drive performance metrics like latency, reliability, and interpretability.Collaborate with cross-functional leaders—product, firmware, backend, customer success—to align AI roadmap with business goals and deployment realities.Recruit top-tier AI and robotics engineering talent, define team structure, and foster a culture of technical excellence and experimentation.MS or PhD in Computer Science, Robotics, ML, EE, or related field along with 8+ years of AI/ML experience. Proven history of delivering multimodal ML systems into production in real-world, safety-sensitive environments (e.g., robotics, autonomous vehicles).Strong expertise across perception, path planning, control systems, and model optimization for resource-constrained platforms.Hands-on technical ability: able to code, train models, debug, and architect systems side-by-side with your team.Leadership experience in startups or fast-moving R&D environments: you’ve built teams, set direction, and scaled initiatives.Track record working with foundation or vision-language-action models, physics-based simulation, or embodied-perception pipelines.Excellent communication: align execs, engineers, and cross-functionally on strategy, trade-offs and results.