- Robot type
- Autonomous Vehicle · Construction
- Location
- San FranciscoCaliforniaUSA
- Job type
- Hardware
- Posted
- Jul 7, 2026
- Salary
- $176,000–$240,000 a year
Full-time
Senior Robotics Planning Engineer
Job description
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.
Job responsibilities
- 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
Job requirements
- BS/MS/PhD in Robotics, Computer Science, or related field required
- 3+ 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
- Experience with multi-agent coordination or scheduling algorithms