Robotics Planning Engineer

Who we are

Pronto AI is a global leader in commercializing autonomous vehicle (AV) technology, deploying Autonomous Haulage Systems (AHS) that automate operations in mines, quarries, and construction sites worldwide. While much of the industry remains in R&D, we deliver real, production-ready autonomy that is already operating in the field. We are on a mission to make mining operations safer, smarter, and more efficient through cutting-edge technology, and we are building toward becoming the world’s first profitable AV technology company.

What you’ll do

• Motion planning — A robust stack, from path planning to trajectory optimization, to generate smooth and safe trajectories for 200+ ton trucks to follow.
• Coordination planning — Systems to simultaneously coordinate the motion of multiple vehicles with intersecting trajectories to avoid collision and maximize throughput.
• Fleet planning — Algorithms that dynamically translate the site-wide state, like loading and dumping locations, to actively managed assignments for each truck.
• Design and implement motion planning algorithms for non-holonomic vehicles
• Develop multi-agent coordination systems that prevent deadlocks and collisions
• 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
• Debug fleet-level issues using logged data and replay tools
• Travel note: This role requires periodic travel to customer sites (up to 5%)
• Schedule note: Some schedule flexibility may be required during deployments

What we’re looking for

• BS/MS/PhD in Robotics, Computer Science, or related field required
• 2+ years of professional (non-internship) software development experience
• Strong foundation in motion planning algorithms
• Experience with computational geometry (collision detection, 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

Preferred Qualifications

• Experience with multi-agent coordination or scheduling algorithms
• Familiarity with Dubins/Reeds-Shepp curves for non-holonomic planning
• Background in trajectory optimization (DCBF, MPC-based planners)
• Experience with graph algorithms (Dijkstra, 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

Technical Environment

• Languages: Python (primary), C++ (performance-critical modules)
• Libraries: NumPy, Shapely, Numba, SciPy
• Testing: Simulation replay, config-driven scenario testing

Why join us

• Work on real, production-deployed autonomy.
• Build technology that directly improves safety, efficiency, and productivity.
• Tackle complex challenges in demanding, real-world environments.
• Be part of a fast-moving team with high ownership and impact.
• See your work deployed and make a difference in the field.
• Collaborate closely with experienced engineers and industry operators.

What else you need to know

• This role is based in our San Francisco office location.
• The base salary range for this role is $119,000 - $161,000 per year.
• Benefits Summary (USA Full-Time Exempt Employees):
• Medical, Dental, Vision, Disability, and Life Insurance
• Flexible Spending Account / Health Savings Account Options
• 401(k)
• Equity
• Sick Time, Unlimited Flexible Time Off, and Paid Holidays
• Paid Parental Leave
• Pre-Tax Commuter Benefit Plan
• Team lunch in our SoMa office every Tuesday and Thursday