Robotics Controls Engineer

While most Autonomous Vehicle (AV) technology companies are stuck in R&D mode, Pronto is a world‑leader in commercializing AV tech via our Autonomous Haulage System, which is automating haulage operations at mines and quarries around the world. Pronto’s team of Silicon Valley veterans has been at the forefront of every major AV development over the past 20 years, with a relentless focus on commercializing the technology, leading to our current specialization in off‑road applications. This focus and our decades of experience have put Pronto on a track to become the world’s first profitable AV technology company.

Our first product is an Autonomous Haulage System (AHS) that enables mines, quarries, and construction sites to deploy autonomous vehicles inside their existing operations to improve site safety and add efficiency gains.

About the Role

We're looking for a Robotics Controls Engineer to develop and maintain the core control systems that enable autonomous haul trucks to operate safely in mining environments. You'll work on localization, path following, longitudinal control, and steering systems that run on 200+ ton vehicles.

What You’ll Build

• Longitudinal Control
• Lateral Control
• Navigation

Responsibilities

• Design, implement, and tune control algorithms for autonomous vehicle systems
• Develop state estimation pipelines that fuse multiple sensor modalities
• Analyze system performance through simulation and field testing
• Debug control issues using logged data and identify root causes
• Collaborate with perception, planning, and hardware teams to integrate control systems
• Write production‑quality Python code that runs reliably and efficiently
• Travel note: This role requires periodic travel to customer sites (up to 15%)
• Schedule note: Some schedule flexibility may be required during deployments

Required Qualifications

• BS/MS/PhD in Robotics, Mechanical Engineering, Aerospace Engineering, Electrical Engineering or related field
• 2+ years of professional (non‑internship) software development experience
• Strong foundation in classical control theory (PID, lead/lag compensation, stability analysis)
• Experience with state estimation (Kalman filters, EKF/UKF)
• Proficiency in Python and NumPy/SciPy for numerical computing
• Understanding of vehicle dynamics and kinematics
• Ability to read and debug real‑time control code
• Experience deploying localization and controls algorithms on real‑world systems

Preferred Qualifications

• Experience with Model Predictive Control (MPC)
• Familiarity with path following algorithms (Stanley, Pure Pursuit)
• Background in signal processing and filter design
• Knowledge of system identification techniques
• Experience with heavy equipment or off‑highway vehicles
• Knowledge of CAN bus and vehicle interfaces
• ROS or similar robotics middleware experience
• Familiarity with modern ML techniques for controls problems

Technical Environment

• Languages: Python (primary), C++ (optimization‑critical paths)
• Libraries: NumPy, SciPy
• Hardware: NVIDIA Jetson, GPS/RTK, IMUs, CAN interfaces
• Testing: Field testing on haul trucks, log replay, simulation

Example Projects

• Tune longitudinal controller gains for a new 100‑ton truck platform accounting for varying payload (0-80 tons) and grade (-15% to +15%)
• Implement anti‑windup and bumpless transfer for switching between throttle and brake control modes
• Create simulations to facilitate control design and continuous integration
• Develop system identification scripts for auto‑tuning controllers
• Develop a Kalman filter that gracefully handles GPS dropouts using IMU dead reckoning

Pronto is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.