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Mariana Minerals is a software-first, vertically integrated minerals company building autonomous mining vehicles to supply critical minerals for energy, AI, and defense technologies. The company combines deep industry expertise with advanced software, automation, and data-driven decision-making to reimagine the minerals supply chain.
As a Machine Learning Engineer (Autonomy), you will develop the autonomy and sensor-integration software enabling mining vehicles to perceive, decide, and drive themselves. You'll work across the full autonomy stack: sensor fusion (LiDAR, cameras, radar, IMU/GNSS), perception, localization, mapping, and motion planning. Your responsibilities include:
- Develop autonomy software focusing on perception, SLAM, motion planning, and/or control for autonomous mining vehicles
- Integrate and calibrate multi-sensor suites, implementing robust sensor fusion and time synchronization for harsh mining environments (dust, vibration, corrosion)
- Build embedded and real-time software bridging sensing, compute, and actuation with emphasis on safety, latency, and reliability
- Develop simulation, logging, and data pipelines to validate autonomy behavior against safety and availability targets
- Conduct bench, rig, and field validation of the autonomy stack, debugging across software-hardware boundaries
- Collaborate closely with hardware, controls, and systems-engineering teams to integrate sensing, compute, and actuation into complete vehicles
You'll carry work from architecture and algorithm design through implementation, simulation, and field validation in a hands-on, first-principles environment. This is an opportunity to develop the world's first fully autonomous mines.
Required qualifications: Bachelor's degree in Mechatronics, Robotics, Computer Science, Electrical Engineering, or related discipline; 2+ years developing autonomy, robotics, or embedded software for mobile robots or vehicles; strong proficiency in C++ and/or Python and robotics middleware (ROS/ROS 2); hands-on experience with sensor integration, fusion, and perception/localization/motion-planning algorithms; working knowledge of real-time and embedded systems, controls, and software-hardware integration. Experience in autonomous vehicles, robotics, automotive, or off-highway equipment is strongly preferred.
