Chief Engineer - ML, Physical AI Autonomy

Chief Engineer - ML, Physical AI, & Autonomy

Location: Kent, WA (preferred) | Denver, CO | Florida | Huntsville, AL | Texas | California | Remote consideration

Security Clearance: Ability to obtain a DoD U.S. Secret clearance. U.S. citizenship required.

Blue Origin is building a world‑class Machine Learning, Physical AI, and autonomy organization to power our next generation of space vehicles, lunar systems, and robotic platforms. Our vision of millions of people living and working in space requires advanced robotics and Physical AI of all kinds. We are seeking a senior ML / Autonomy / Physical AI technical leader to anchor this capability — architecting and training the models that will enable autonomous operations on the lunar surface and across our space systems.

You will lead a focused team of 6-8 engineers, define the Digital Twin simulation and training pipeline, train and architect models, deploy them onto our platforms and infrastructure, and shape Blue Origin's strategy in this area. You will engage with peers in academia, industry, and government and report to senior leadership.

• Model Architecture & Training:
  Lead design and training of ML models for autonomy, perception, decision‑making, and control in space applications
• Digital Twin & Simulation:
  Define the simulation and training pipeline needed for the different lunar surface and in‑space applications
• Platform Integration:
  Operationalize models — deploy, run, and integrate into Blue Origin systems and infrastructure
• Team Building:
  Recruit, build, and lead a focused team of 6‑8 ML/autonomy engineers
• Technical Strategy:
  Define autonomy reference architectures spanning lunar surface operations, in‑space servicing, autonomous landing, and orbital robotics
• Cross‑Functional Integration:
  Partner with GN&C, avionics, software, and systems engineering to translate research advances into deployable autonomy
• Assured Autonomy:
  Champion V&V, runtime assurance, uncertainty quantification, and safety cases for high‑consequence space systems
• External Engagement:
  Represent Blue Origin with customers, partners, and academia
• Executive Visibility:
  Brief Executive leadership on autonomy capability and roadmap

• M.S. in Computer Science, Electrical/Computer Engineering, Aerospace Engineering, Robotics, Applied Math, or related technical field
• 12+ years (Level
  7) / 10+ years (Level
  6) of progressive experience developing autonomy, robotics, or ML systems for real‑world deployment
• Industry leader in developing AI/ML models and training techniques for physical AI
• Demonstrated technical leadership of complex multi‑disciplinary efforts
• Deep expertise in two or more of the following:
  • Model architectures and training techniques for Physical AI systems
  • Computer vision and perception (detection/segmentation, SLAM, visual‑inertial odometry, sensor fusion)
  • Robotic manipulation, grasping, and contact‑rich tasks
  • Modern ML stack (PyTorch / JAX / Tensor Flow), training pipelines, and model deployment
  • Decision‑making under uncertainty (RL, MPC, MDP/POMDP, hybrid planning)
  • GN&C‑integrated autonomy (rendezvous & proximity operations, hazard detection & avoidance, terrain‑relative navigation, powered descent guidance)
  • Multi‑agent / swarm systems and distributed autonomy
• Production‑quality coding skills in Python and C/C++
• Experience taking concepts from research through integrated demonstration
• Excellent technical communication; able to brief executives, customers, and engineers

• Ph.D. in a relevant technical field
• Prior automotive / AV autonomy, aerospace, defense, or safety‑critical systems experience
• Experience with foundation models / Vision‑Language‑Action (VLA) models for robotics
• Familiarity with V&V for ML/AI in high‑consequence applications (formal methods, runtime monitors, uncertainty quantification, SOTIF/ISO 21448)
• Experience with simulation frameworks:
  Isaac Sim, Gazebo / Ignition, Mu Jo Co , MATLAB/Simulink, custom physics engines
• Experience with ROS / ROS2, DDS, or analogous middleware
• Experience deploying ML on edge / embedded / radiation‑tolerant compute (Orin, Versal, rad‑hard SoCs, FPGAs)
• Familiarity…