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Loading LAYIQ…From Teleo's posting. “We” and “our” refer to the employer.
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 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.
The Team: You will lead engineers across the following areas. Sizes will shift as priorities change.
camera and lidar fusion, off-road segmentation, detection and tracking, localization and mapping, auto-labeling
machine and terrain simulation, material interaction, scenario generation, sim-to-real validation
system identification, MPC, learned and hybrid controllers across tracked and wheeled platforms
motion and task planning for dozers, loaders, excavators, and skid steers on unstructured sites
multi-machine coordination, task allocation, and the interface to remote operators
RL, imitation learning from operator data, and VLA-style models for material manipulation
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.
LAYIQ is an independent job-discovery service. This listing does not imply a partnership with or endorsement by the employer. Review the original posting for current details and availability.
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