Principal Motion Planning Engineer

Fruition Group US; California (MO); On-site; USD 180,000 - 240,000; Full time

Job summary

Fruition Group US is seeking a Principal Motion Planning Engineer to provide technical leadership for next-generation autonomous driving systems. This role will own complex planning problems from architecture and algorithm development through simulation, validation and production deployment.

You will lead development of behavior planning, trajectory generation and optimization, and mentor engineers while shaping long-term technical strategy across the planning stack.

Qualifications

• Experience in autonomous driving or robotics focused planning.
• Proven ability to design and optimize planning systems.
• Strong programming skills in C++/Python.

Responsibilities

• Lead architecture and development of behavior planning, trajectory generation and motion optimization systems.
• Develop safe, dynamically feasible trajectories for highway and urban scenarios.
• Address complex maneuvers including lane changes, mergers, intersections, obstacle avoidance and emergencies.
• Integrate perception, prediction, localization and control with planning stack.
• Develop planning approaches considering uncertainty and vehicle dynamics.
• Analyze real-world autonomy failures and translate findings into improvements.
• Build simulation and evaluation frameworks for large-scale planner validation.
• Provide technical mentorship and influence planning architecture and long-term strategy.

Skills

Motion planning

Behavior planning

Trajectory generation

Optimization

C++

Python

MPC

QP/NLP

Job description

We are seeking a Principal Motion Planning Engineer to provide technical leadership for next-generation autonomous driving systems. This role will own complex planning problems from architecture and algorithm development through simulation, validation and production deployment.

Responsibilities

• Lead architecture and development of behavior planning, trajectory generation and motion optimization systems.
• Develop safe, comfortable and dynamically feasible trajectories across complex highway and urban scenarios.
• Address challenging behaviours including lane changes, merging, intersections, obstacle avoidance and emergency manoeuvres.
• Integrate perception, prediction, localization and vehicle-control interfaces into the planning stack.
• Develop planning approaches that account for uncertainty, vehicle dynamics and surrounding-agent behavior.
• Analyze real-world autonomy failures and translate findings into planning improvements.
• Build simulation and evaluation frameworks for large-scale planner validation.
• Provide technical mentorship and influence planning architecture and long-term technical strategy.

Requirements

• 6 - 10+ experience in autonomous driving, robotics or motion planning.
• Deep expertise in motion planning, behavior planning, trajectory generation and optimization.
• Strong C++ and Python skills.
• Experience with MPC, QP/NLP optimization, trajectory optimization and/or sampling-based planning.
• Strong understanding of vehicle dynamics and the perception → prediction → planning → control pipeline.
• Experience deploying planning algorithms on real autonomous vehicles.
• Learning-based planning, RL or imitation learning.