Senior Robotics Engineer

Caterpillar•Irving, TX

1d•Onsite

About The Position

Caterpillar is hiring a robotics generalist to develop autonomy software that enables large off-road machines to operate autonomously at customer sites. The role spans the autonomy stack, from perception through motion planning and control, using both learning-based methods and classical robotics foundations. The engineer will own components end-to-end, taking them from ideas and prototypes through production deployment on real hardware, and will contribute broadly while bringing depth in at least one specialty. The position is based onsite at Caterpillar’s Irving, Texas office, five days per week. Domestic relocation assistance and visa sponsorship are available.

Requirements

Extensive professional engineering experience, with an emphasis on robotics.
Robotics generalist comfortable working across the autonomy stack.
Expertise in at least one of AI, motion planning, perception, controls, or SLAM.
Production-quality C++ and Python skills.
Experience with ROS or similar middleware in real robotics systems.
Full-lifecycle product experience, ideally taking robotics products from idea to production.
Pragmatic, first-principles engineering approach, with end-to-end component ownership and collaboration across a fast-moving delivery team.
Bachelor’s degree in Computer Science, Engineering, or a similar field.
Ability to work onsite at the Irving, Texas office five days per week.

Nice To Haves

Experience in real-world or field robotics, or autonomous vehicles, on-road or off-road.
Experience with learning-based control or perception, or foundation/VLA-style models.
Experience with simulation and on-vehicle deployment.
MLOps or training-infrastructure depth for an ML-leaning profile.
Interest in working on site and seeing software operate on real machines.

Responsibilities

Participate in test review and analysis, test witnessing, and certification of robotics software.
Design, build, and ship autonomy components across perception, planning, control, and learning.
Take work from prototype through production on real hardware.
Bring depth in a specialty while contributing across the autonomy stack.
Work in small, outcome-owning pods staffed from capability benches.