Jobs / United States / Pronto Technology INC

Pronto Technology INC

Senior Robotics Planning Engineer

San Francisco, CA Posted 24 days ago

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Skills this job asks for

PythonRedisMachine learningC++

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Sponsorship verdict

Sponsorship possible

One solid signal, not two. Worth applying, and worth asking about sponsorship early.

  • Employer is on a government sponsor recordUSCIS Data Hub records 1 H-1B approvals for this employer in FY2023 — older 2023 data; no recent Department of Labor filings (Oct 2025 – Jun 2026) were found for it.
  • The posting doesn’t mention sponsorshipSilence isn’t a refusal — ask the recruiter before investing much time.
  • No salary bar for this routeH-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area.
  • Confirmed live todayWhen a source last listed this job as open.
Details and sources
Employer is on a government sponsor record
USCIS Data Hub records 1 H-1B approvals for this employer in FY2023 — older 2023 data; no recent Department of Labor filings (Oct 2025 – Jun 2026) were found for it. Source: US Department of Labor visa filings (LCA) (US Department of Labor (OFLC), plus USCIS H-1B Employer Data Hub).
No salary bar for this route
H-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area. Cap-subject employers enter a lottery weighted by wage level. Source: https://www.federalregister.gov/documents/2025/12/29/2025-23853/weighted-selection-process-for-registrants-and-petitioners-seeking-to-file-cap-subject-h-1b, rules effective 2026-02-27.

US H-1B: cap-subject employers enter a lottery weighted by wage level — Level I gets 1 entry, Level IV gets 4 (DHS projected selection odds ≈15% at Level I to ≈61% at Level IV). Universities and non-profit research employers are cap-exempt. The $100,000 fee for new petitions from abroad is currently blocked by a court order (appeal pending).

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About the role

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 We're looking for a Robotics Planning Engineer to develop the high-level autonomy systems that coordinate fleets of autonomous haul trucks in mining environments. You'll 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. • 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 • 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 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 making 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. As a co

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