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 systemsDevelop state estimation pipelines that fuse multiple sensor modalitiesAnalyze system performance through simulation and field testingDebug control issues using logged data and identify root causesCollaborate with perception, planning, and hardware teams to integrate control systemsWrite production‑quality Python code that runs reliably and efficientlyTravel note : This role requires periodic travel to customer sites (up to 15%)Schedule note : Some schedule flexibility may be required during deploymentsRequired Qualifications
BS / MS / PhD in Robotics, Mechanical Engineering, Aerospace Engineering, Electrical Engineering or related field2+ years of professional (non‑internship) software development experienceStrong 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 computingUnderstanding of vehicle dynamics and kinematicsAbility to read and debug real‑time control codeExperience deploying localization and controls algorithms on real‑world systemsPreferred Qualifications
Experience with Model Predictive Control (MPC)Familiarity with path following algorithms (Stanley, Pure Pursuit)Background in signal processing and filter designKnowledge of system identification techniquesExperience with heavy equipment or off‑highway vehiclesKnowledge of CAN bus and vehicle interfacesROS or similar robotics middleware experienceFamiliarity with modern ML techniques for controls problemsTechnical Environment
Languages : Python (primary), C++ (optimization‑critical paths)Libraries : NumPy, SciPyHardware : NVIDIA Jetson, GPS / RTK, IMUs, CAN interfacesTesting : Field testing on haul trucks, log replay, simulationExample 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 modesCreate simulations to facilitate control design and continuous integrationDevelop system identification scripts for auto‑tuning controllersDevelop a Kalman filter that gracefully handles GPS dropouts using IMU dead reckoningPronto 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.
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