Summary
What you’ll impact
The organization is seeking a Machine Learning Engineer (Autonomy) to develop autonomy and sensor‑integration software for fully autonomous mining vehicles. The role involves designing, implementing, and validating perception, localization, mapping, and motion‑planning systems, while collaborating closely with hardware, controls, and systems‑engineering teams.
Responsibilities
What you'll do
- Develop autonomy software for autonomous mining vehicles focusing on one or more area: perception, SLAM, motion planning, and control
- Integrate and calibrate the sensing suite (LiDAR, cameras, radar, IMU, GNSS), implementing sensor fusion and time synchronization robust to dust, vibration, and corrosion-heavy mining environments
- Build and maintain embedded and real-time software that bridges sensing, compute, and actuation, with attention to safety, latency, and reliability
- Develop simulation, logging, and data pipelines to test autonomy behavior and drive performance against safety and availability targets
- Lead bench, rig, and field validation of the autonomy stack, debugging across the full software-hardware boundary
- Collaborate with hardware and controls engineers to integrate sensing, compute, and actuation into a complete vehicle
Requirements
What you’ll bring
- Bachelor's degree in Mechatronics, Robotics, Computer Science, Electrical, or related engineering discipline
- 5-10+ years developing autonomy, robotics, or embedded software, ideally for mobile robots or vehicles
- Strong proficiency in C++ and/or Python, and with a robotics middleware such as ROS/ROS 2
- Hands-on experience with sensor integration and fusion - LiDAR, cameras, radar, IMU, GNSS - and with perception, localization, or motion-planning algorithms
- Working knowledge of real-time and embedded systems, and of the controls and software-hardware integration that drive actuation
- Experience in autonomous vehicles, robotics, automotive, or off-highway equipment strongly preferred