Gravis Robotics is a high-growth Series A start-up backed by SoftBank, bringing Physical AI to the construction industry, turning heavy construction machines into autonomous robots. Gravis began as an ETH Zurich spin-out, and our unique combination of learning-based automation and augmented remote control lets one operator safely conduct a fleet of earthmoving machines in a gamified environment. Backed by deep robotics research and now deployed across multiple countries with leading construction and equipment partners, our team is rapidly growing to bring this technology to a trillion-dollar industry. At Gravis, we engineer solutions at the nexus of hardware and software every day: bringing new perception and control technologies onto powerful, autonomous machines. Our Rooftop Autonomous Control Kit (Rack) combines sensors, compute, communication and networking modules toward a manufacturer-agnostic solution that can be applied to a variety of construction machines regardless of type and age. We are seeking a skilled Global Dynamic Mapping and SLAM Engineer for our perception team: you will help design, develop, test and deploy customized forms of state-of-the-art localization+mapping, state estimation and calibration algorithms—while ensuring production quality implementation and timely execution. A central focus of the role will be the development of global dynamic mapping systems: building and maintaining consistent, scalable, and semantically meaningful maps of active construction sites as they evolve over time. You will work on methods that fuse lidar, inertial, visual, GPS/GNSS, and fleet-level data to support localization, autonomy, remote operation, site understanding, and long-term map maintenance across multiple machines.