Planning Engineer

Foundation

  • San Francisco, California
  • 5 days ago

    Highlights

    Generate speed profiles from curvature, visibility, slope, and surface quality; respect slow/no-go zones and grade limits. Proficiency in ROS2, C++, Python, internal middleware, and point cloud / occupancy representations, map / cost representations.

    Numbers & Facts

    LocationSan Francisco, California

    Description

    Who should join:

    • You deeply believe that this is the most important mission for humanity and needs to happen yesterday.
    • You are highly technical - regardless of the role you are in. We are building technology; you need to understand technology well.
    • You care about aesthetics and design inside out. If it's not the best product ever, it bothers you, and you need to “fix” it.
    • You don't need someone to motivate you; you get things done.

    Why We Are Hiring for This Role:

    • Set short and long term direction for planning architecture and priorities. 
    • Design and implement motion planning algorithms for off-road ATV navigation.
    • Integrate waypoints, obstacle avoidance, and terrain constraints into safe, drivable paths.
    • Tune and validate control parameters for robust performance on rough, off-road terrain.
    • Design test scenarios and evaluate planning algorithms in both simulation and field environments.
    • Set real-time replanning policies and continuity rules so behavior remains stable as conditions change.
    • Generate speed profiles from curvature, visibility, slope, and surface quality; respect slow/no-go zones and grade limits.
    • Collaborate with vehicle engineering to create an integrated system, including sensor/compute selection and integration.
    • Implement state-of-the-art approaches to trajectory planning, route planning, and real-time control. 

    What Kind of Person We Are Looking For:

    • Strong background in robotics, controls, or related fields (MSc or equivalent experience).
    • Bachelor’s Degree or Master’s Degree candidate in Computer Science, Math, Electrical.
    • Hands-on experience with motion planning algorithms.
    • Proficiency in ROS2, C++, Python, internal middleware, and point cloud / occupancy representations, map / cost representations.
    • Solid grasp of vehicle dynamics and path-following control.
    • Comfort with real-world testing and debugging on robotic platforms.
    • Experience integrating autonomy stacks on real robotic vehicles (not just simulation).
    • Strong problem-solving skills with a bias toward practical, field-ready solutions over theory.
    • Understanding of ADAS/AD systems and vehicle dynamics is a plus

    Benefits:

    • We provide market standard benefits (health, vision, dental, 401k, and equity, etc.). Join us for the culture and the mission, not for the benefits.

    Salary:

    • The annual compensation is expected to be between $150,000 - $195,000. Exact compensation may vary based on skills, experience, and location

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