Software Engineer - Motion Planning (fallback Stack)

Applied Intuition Applied Intuition · Robotics · Sunnyvale, CA · SDS Software Engineering

Software Engineer role focused on designing and implementing classical motion planning systems for autonomous vehicles, emphasizing deterministic behavior and large-scale evaluation. The role involves building safety-critical planning systems that operate reliably under degraded conditions, using simulation and real-world data for evaluation and tuning.

What you'd actually do

  1. Design and implement classical or ML motion planners for fallback and minimal-risk maneuvers
  2. Build planners that operate reliably under degraded perception, partial observability, and system faults
  3. Define and execute safe, deterministic vehicle motions such as controlled slow-downs, pull-overs, and safe stops
  4. Use large-scale simulation and real-world data to evaluate planner behavior and guide parameter tuning
  5. Develop metrics, analysis tools, and dashboards to understand planner performance at scale

Skills

Required

  • motion planning for autonomous vehicles or robotics
  • robotic motion planning algorithms and trajectory generation
  • deterministic, safety-critical planning systems
  • data-driven mindset for large-scale evaluation, debugging, and tuning
  • C++
  • real-time systems
  • systems thinking
  • cross-functional collaboration

Nice to have

  • minimal-risk maneuvers (MRM) or emergency handling behaviors
  • AV safety concepts, ODD constraints, or safety-case-driven development
  • ML techniques for parameter tuning, calibration, or offline optimization
  • degraded sensors, uncertainty, or human-in-the-loop systems
  • simulation frameworks
  • large-scale log analysis

What the JD emphasized

  • classical motion planning
  • deterministic, safety-critical planning systems
  • large-scale evaluation
  • classical or ML motion planners
  • deterministic vehicle motions
  • large-scale evaluation
  • planner performance at scale
  • 5+ years of experience in motion planning for autonomous vehicles or robotics
  • Strong foundation in robotic motion planning algorithms and trajectory generation
  • Experience building deterministic, safety-critical planning systems
  • A data-driven mindset for large-scale evaluation, debugging, and tuning of planning behavior
  • Proficiency in C++ and experience working in real-time systems