Machine Learning Engineer (Autonomy)

Responsibilities

• Develop autonomy software for autonomous mining vehicles in perception, SLAM, motion planning, and control.
• Integrate and calibrate LiDAR, cameras, radar, IMU, and GNSS sensors, including sensor fusion and time synchronization.
• Build and maintain embedded and real-time software connecting sensing, compute, and actuation with emphasis on safety, latency, and reliability.
• Develop simulation, logging, and data pipelines to test autonomy behavior and measure safety and availability performance.
• Conduct bench, rig, and field validation of the autonomy stack and debug across the software-hardware boundary.
• Collaborate with hardware and controls engineers to integrate sensing, compute, and actuation into complete vehicles.

Requirements

• Bachelor's degree in Mechatronics, Robotics, Computer Science, Electrical, or a related engineering discipline.
• At least 2 years of experience developing autonomy, robotics, or embedded software, ideally for mobile robots or vehicles.
• Strong proficiency in C++ and/or Python and experience with robotics middleware such as ROS or ROS 2.
• Hands-on experience with sensor integration and fusion involving LiDAR, cameras, radar, IMU, and GNSS.
• Experience with perception, localization, or motion-planning algorithms.
• Working knowledge of real-time and embedded systems, controls, and software-hardware integration for actuation.
• Experience in autonomous vehicles, robotics, automotive, or off-highway equipment is strongly preferred.