Gravis Robotics is a startup turning heavy construction machines into intelligent and autonomous robots. Our unique combination of learning-based automation and augmented remote control enables a single operator to safely manage a fleet of earthmoving machines in a gamified environment. With over a decade of academic experience at the cutting edge of large-scale robotics, our team is rapidly translating this expertise into real-world deployments with industry leaders in a trillion-dollar market.
At Gravis, the intelligence behind our machines is only as good as the systems that develop, train, and operate it. The Gravis Rack fuses data from LiDAR, cameras, GNSS, and hydraulics into a learning-based control system that adapts in real time to changing ground conditions. As our fleet grows and our models become more sophisticated, we need world-class infrastructure to support the full ML lifecycle: from raw sensor data ingestion on the edge to continuous model training, evaluation, and deployment at scale.
As our Data & ML Ops Engineer, you will be driving the requirements gathering, development, rollout and operation of the related infrastructure. The systems you build and operate power every ML experiment, training run, and production deployment at Gravis. You will work at the intersection of our Platform, Autonomy, and Perception teams to enable high velocity & quality ML development & deployment.