Robotics Planning Engineer (All levels)

About Pronto AI

Pronto AI is a global leader in commercializing autonomous vehicle technology, deploying Autonomous Haulage Systems that automate operations in mines, quarries, and construction sites worldwide. While much of the industry remains in R&D, Pronto delivers real, production-ready autonomy already operating in the field.

The mission is to make mining operations safer, smarter, and more efficient — and to build toward becoming the world’s first profitable AV technology company. This is production autonomy, not a research project.

The Opportunity

Pronto AI is looking for a Robotics Planning Engineer to develop the high-level autonomy systems that coordinate fleets of autonomous haul trucks in mining environments. You will work on path planning, multi-vehicle coordination, and dispatch systems that operate at the site level — deciding where trucks go, when they go, and how they interact with each other at scale.

The planning stack spans three layers: motion planning to generate smooth, safe trajectories for 200+ ton trucks; coordination planning to simultaneously manage multiple vehicles with intersecting trajectories to avoid collision and maximize throughput; and fleet planning to dynamically translate site-wide state into active assignments for each truck. Your work will be deployed in the field, not in simulation.

What You’ll Do

• Design and implement motion planning algorithms for non-holonomic vehicles
• Develop multi-agent coordination systems that prevent deadlocks and collisions across large truck fleets
• Build simulation and visualization tools for validating planning algorithms
• Optimize planning algorithms for real-time performance in production environments
• Collaborate with controls engineers to ensure planned paths are executable on real hardware
• Debug fleet-level issues using logged data and replay tools

Travel up to 5% to customer sites; some schedule flexibility required during deployments.

You Should Have

• BS, MS, or PhD in Robotics, Computer Science, or a related field
• 2+ years of professional software development experience (non-internship)
• Strong foundation in motion planning algorithms
• Experience with computational geometry including collision detection and polygon operations
• Proficiency in Python and NumPy for numerical computing
• Understanding of vehicle kinematics and nonholonomic constraints
• Ability to analyze algorithm complexity and optimize for real-time performance

Nice to Have

• Experience with multi-agent coordination or scheduling algorithms
• Familiarity with Dubins or Reeds-Shepp curves for non-holonomic planning
• Background in trajectory optimization using DCBF or MPC-based planners
• Experience with graph algorithms such as Dijkstra or heuristic search
• Knowledge of GEOS, Shapely, or other computational geometry libraries
• Experience with fleet management or dispatch systems
• Familiarity with Redis, ZeroMQ, or similar infrastructure
• Familiarity with modern ML techniques for planning problems

Compensation and Benefits

Base salary depending on experience, plus equity.

Benefits include medical, dental, vision, disability, and life insurance; FSA/HSA options; 401(k); unlimited flexible time off and paid holidays; paid parental leave; pre-tax commuter benefit; and team lunches in the SoMa office twice a week.