Senior Software Engineer - Planning
$60k - $300k • Tokyo • FullTime
Posted 2mo ago
Remote Work Policy
On-site
Employment Type
FullTime
Categories
Applied AI Engineer
About the job
Applied Intuition is seeking a Motion Planning Engineer to design and ship deterministic, safety-critical planning systems for autonomous vehicles. This role focuses on classical motion planning, predictable behavior, and large-scale evaluation, rather than deep learning-driven planning. You will contribute to and learn from best practices in the nascent autonomy industry, working in a dynamic, customer-focused team. If you are hands-on and looking for a place to have a multiplying effect on making autonomous systems a reality, Applied is the place for you!
Responsibilities
- Design and implement classical or ML motion planners for fallback and minimal-risk maneuvers.
- Build planners that operate reliably under degraded perception, partial observability, and system faults.
- Define and execute safe, deterministic vehicle motions such as controlled slow-downs, pull-overs, and safe stops.
- Use large-scale simulation and real-world data to evaluate planner behavior and guide parameter tuning.
- Develop metrics, analysis tools, and dashboards to understand planner performance at scale.
- Collaborate closely with behavior prediction, perception, controls, safety, and remote assistance teams.
- Contribute to a reusable fallback platform used across trucking and other autonomy programs.
Requirements
- 5+ years of experience in motion planning for autonomous vehicles or robotics.
- Strong foundation in robotic motion planning algorithms and trajectory generation (optimization-, search-, or rule-based).
- 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.
- Strong systems thinking and cross-functional collaboration skills.
- Experience designing minimal-risk maneuvers (MRM) or emergency handling behaviors (nice to have).
- Familiarity with AV safety concepts, ODD constraints, or safety-case-driven development (nice to have).
- Experience using ML techniques for parameter tuning, calibration, or offline optimization (nice to have).
- Experience working with degraded sensors, uncertainty, or human-in-the-loop systems (nice to have).
- Background in simulation frameworks or large-scale log analysis (nice to have).