Machine Learning Engineers (Autonomy)

Location: Hybrid work in San Francisco, CA; Ann Arbor, MI; or Houston, TX

Salary: $140,000–$180,000 estimated annual base salary, plus equity. Final salary depends on experience, location, and other factors.

Company

hirify.global is a software-first, vertically integrated minerals company developing advanced software, automation, and data-driven systems for critical-minerals supply chains.

What you will do

• Develop autonomy software for mining vehicles across perception, SLAM, motion planning, and control.
• Integrate and calibrate LiDAR, cameras, radar, IMU, and GNSS, including sensor fusion and time synchronization for harsh mining environments.
• Build embedded and real-time software connecting sensing, compute, and actuation with attention to safety, latency, and reliability.
• Develop simulation, logging, and data pipelines to evaluate autonomy behavior against safety and availability targets.
• Validate the autonomy stack on benches, rigs, and in the field, debugging across software and hardware boundaries.
• Collaborate with hardware, controls, and systems-engineering teams to integrate complete autonomous vehicles.

Requirements

• Bachelor’s degree in Mechatronics, Robotics, Computer Science, Electrical Engineering, or a related 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.

Nice to have

• Experience in autonomous vehicles, robotics, automotive, or off-highway equipment.

Culture & Benefits

• Equity offered in addition to base salary.
• Safety is prioritized over speed or cost.
• Emphasis on ownership, practical automation, open collaboration, and knowledge sharing.