Senior Manager, AI Perception and Skills

Agility Robotics Agility Robotics · Robotics · Remote · Innovation

Senior Manager of AI Perception and Skills for humanoid robots, leading teams focused on real-time object detection, scene understanding, and learning from demonstration. The role involves end-to-end delivery from research to production deployment on robot hardware, accelerating data flywheel strategy, and building high-performing teams. Focus is on applied research and engineering with production impact within a one-year horizon.

What you'd actually do

  1. Lead end-to-end delivery of AI Perception and Skills capabilities, from research conception through production deployment on robot hardware.
  2. Own the roadmap and success of both teams, setting clear goals and holding yourself and the team accountable for quality, reliability, and pace.
  3. Accelerate our data flywheel strategy — combining teleoperation, synthetic data, and fleet learning — to systematically expand robot performance and reliability at scale.
  4. Champion your team's talent, represent their needs to senior leadership, and foster an inclusive environment where engineers feel safe to experiment and learn from failure.
  5. Drive performance cycles, build individualized development plans, and lead hiring to grow both teams with high-caliber researchers and engineers.

Skills

Required

  • Advanced degree (M.S. or Ph.D.) in Computer Science, Robotics, Electrical Engineering, or a related field.
  • 8+ years of experience in AI/ML, with 3+ years managing engineering or research teams.
  • Demonstrated experience shipping real-time AI systems in robotics, autonomous vehicles, or other mission-critical domains.
  • Deep technical expertise in computer vision and learning-from-demonstration (e.g., imitation learning, behavior cloning).
  • Experience deploying models on resource-constrained edge hardware, with practical knowledge of inference optimization, power, and thermal constraints.
  • Proven ability to build and scale high-performing teams, including hiring, mentorship, and organizational development.

Nice to have

  • Experience with teleoperation systems for robot data collection or remote operation
  • Experience with humanoid or legged robot platforms in research or production settings
  • Experience fine-tuning or adapting foundation models (vision-language, diffusion policy, etc.) for robotics applications

What the JD emphasized

  • shipping real-time AI systems in robotics
  • deploying models on resource-constrained edge hardware

Other signals

  • shipping production AI systems
  • real-time perception
  • learning from demonstration
  • deploying models on edge hardware
  • scaling teams