Machine Learning Engineer (Autonomy)
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- Work arrangement
- hybrid
- Employment
- FullTime
- Stated compensation
- USD 140,000–180,000 1 YEAR
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Requirements
1 with evidence8 unclear or unstated- Remote policy
- hybrid
“Provider workplace type: hybrid”
From employer posting metadata - Employment type
- FullTime
- Compensation
- USD 140,000–180,000 1 YEAR
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- Geographic scope
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- Degree requirement
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Original job description
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Mariana Minerals is a software-first, vertically integrated minerals company on a mission to supply the critical minerals powering modern energy, AI, and defense technologies. We’re reimagining the minerals supply chain by combining deep industry expertise with advanced software, automation, and data-driven decision-making.
Role OverviewWe are hiring Machine Learning Engineers (Autonomy) to build the autonomy and sensor-integration software that lets our mining vehicles perceive, decide, and drive themselves.
In this role you will work on parts of the software and sensor integration that enables full mining autonomy — sensor fusion across LiDAR, cameras, radar, and IMU/GNSS; perception, localization, and mapping; and the autonomy stack that turns sensing into safe vehicle motion. You will carry work from architecture and algorithm design through implementation, simulation, and bench and field validation, working hand in hand with our hardware, controls, and systems-engineering teams. This is a hands-on, first-principles role for an engineer who wants to develop the world’s first fully autonomous mines.
What You’ll DoDevelop 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
Build 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
Bachelor's degree in Mechatronics, Robotics, Computer Science, Electrical, or related engineering discipline
2+ 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
Our culture is built on four principles:
Everyone Gets Home Safe. We never put speed or cost ahead of people.
Extreme Ownership. We take full responsibility for outcomes, relentlessly driving toward solutions.
Engineer Out Requirements, then Automate. We simplify, optimize, and then automate for scale.
Share Your Legos. We collaborate openly, share knowledge, and empower each other to build bigger, better solutions.
Join us as we build the future of responsible mineral sourcing and supply!
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