Head of Autonomy

Teleo, a Havoc company, is a robotics company that transforms construction heavy equipment, including loaders, dozers, excavators, and trucks, into autonomous robots for commercial and defense applications. Our technology enables a single operator to supervise and control multiple machines simultaneously, delivering significant productivity gains while improving operator safety and comfort.

Teleo was founded by a team of experienced technology leaders who previously led the development of Lyft's Self-Driving Car program and Google Street View. Teleo recently announced its merger with Havoc AI, a fast-growing defense technology company developing coordinated fleets of autonomous maritime vessels.

This is a unique opportunity to join a team building technology with real-world impact. You will work on cutting-edge 100,000-pound autonomous robots and engineer complex systems at the intersection of hardware, software, robotics, and AI.

The Role

The Head of Autonomy owns Teleo's autonomy stack end to end and leads the team that builds it. You will lead the engineering team across perception, simulation, controls, path planning, fleet orchestration, learning-based methods (RL, imitation learning, and VLA-style models), and MLOps.

This is a senior player-coach role. You will set the technical direction, make the architecture calls, and stay close enough to the code and the field data to review designs in depth. You will also hire, grow, and run the team, and be accountable for autonomy performance on customer deployments across several machine types.

The core technical problem is taking a stack that works today in supervised autonomy on real job sites and scaling it: more machine types, more sites, more material-manipulation tasks, and fewer operator interventions per hour, without compromising safety.

Core Responsibilities

The Team

• Perception: camera and lidar fusion, off-road segmentation, detection and tracking, localization and mapping, auto-labeling
• Simulation: machine and terrain simulation, material interaction, scenario generation, sim-to-real validation
• Controls: system identification, MPC, learned and hybrid controllers across tracked and wheeled platforms
• Path planning: motion and task planning for dozers, loaders, excavators, and skid steers on unstructured sites
• Fleet orchestration: multi-machine coordination, task allocation, and the interface to remote operators
• Learning-based autonomy: RL, imitation learning from operator data, and VLA-style models for material manipulation
• MLOps: data pipelines, training infrastructure, model evaluation, and deployment to the fleet

Requirements

• M.S. or Ph.D. in Robotics, Computer Science, Electrical or Mechanical Engineering, or a related field, or equivalent experience
• 10+ years building autonomy or robotics software, with at least 5 years managing engineering teams, including managers or technical leads
• Shipped autonomy that runs on physical robots or vehicles in real operating conditions, not only in simulation
• Hands-on depth in at least two of: perception, planning, controls, simulation, or learning-based control, and working fluency across the full stack
• Practical experience with learning-based methods (imitation learning, RL, or large pretrained models) and a clear view of where they beat classical approaches and where they don't
• Built or run data and evaluation infrastructure that tied model changes to field performance
• Strong C++ and Python; able to review code and designs at a senior engineer's level
• Experience deploying autonomy and ML models on embedded compute (NVIDIA Jetson-class or similar)
• Track record of hiring and developing strong engineers
• Comfortable working on-site in Palo Alto and spending time in the field on job sites and test areas
• Must be a U.S. person (U.S. citizen or lawful permanent resident) due to export control requirements

Preferred Qualifications

Bonus Points

Teleo is an equal opportunity employer and we value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. All qualified people are encouraged to apply.

Compensation: USD 250,000 – 300,000 per year salary