About this role
- Procedural scene generation in simulation (terrain, lighting, asset placement)
- Synthetic data generation for training ML models across varied environmental conditions
- Enhancement of physics-based sensor models for LiDAR and cameras
- Automated test creation in simulation for construction site scenarios and machine behaviors (e.g. excavation with truck loading)
- Master's level study (e.g. in robotics, computer science, mechanical or electrical engineering)
- Advanced proficiency in Python
- Working knowledge of C++
- Experience with ML pipelines and 3D perception (e.g. object detection, point cloud processing)
- Experience with robotics simulation tools (e.g. Gazebo, MuJoCo, NVIDIA Isaac Sim)
- Experience with ROS 2 or other robotics frameworks
- Proficiency in Linux and Git
- Familiarity with sensor modeling (LiDAR, cameras) or synthetic data generation
- Experience conducting research (e.g. through an academic lab or previous internships)
- Interest or prior experience in heavy construction or autonomous vehicles
- Experience with software testing (unit, component, or functional tests)
Tech stack
PythonC++
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