Machine Learning Engineer (Autonomy)

Mariana Minerals

$130K — $160K *
Aerospace & Defense
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • Bachelor's degree in Mechatronics, Robotics, Computer Science, Electrical, or related engineering discipline
  • 2+ years in autonomy, robotics, or embedded software development, preferably for mobile robots or vehicles
  • Proficiency in C++ and/or Python, with experience in robotics middleware like ROS/ROS 2
  • Hands-on experience with sensor integration and fusion including LiDAR, cameras, radar, IMU, GNSS
  • Knowledge of real-time and embedded systems, particularly in control and software-hardware integration
  • Experience in autonomous vehicles, robotics, automotive, or off-highway equipment is strongly preferred

Responsibilities

  • Develop autonomy software focusing on perception, SLAM, motion planning, and control for mining vehicles
  • Integrate and calibrate sensors, implementing robust sensor fusion and time synchronization under challenging conditions
  • Create and maintain embedded, real-time software addressing safety, latency, and reliability requirements
  • Establish simulation, logging, and data pipelines to evaluate autonomy performance against safety and availability targets
  • Conduct validation of the autonomy stack through bench, rig, and field testing, debugging the software-hardware interface
  • Collaborate with hardware and controls engineers to achieve a complete integration of sensing, computing, and actuation into vehicles

Benefits

  • Opportunities for hands-on development in a cutting-edge technology area
  • Collaborative work environment with cross-functional teams
  • Chance to contribute to pioneering fully autonomous mining operations
  • Potential for career advancement in a growing industry
  • Engagement with advanced robotics and sensor technology in real-world applications
Full Job Description
Role Overview

We 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 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
  • 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


What You'll Bring
  • 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

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