Motion Planning Lead Engineer

Job Responsibilities

Lead the design, development, and integration of advanced motion planning algorithms for autonomous systems.
Architect and implement robust behavior planning, trajectory optimization, and speed planning modules using C++.
Drive cross‑functional collaboration with perception, control, and software teams to ensure seamless system integration.
Oversee simulation testing, validation, and data‑driven debugging of planning pipelines.
Mentor and guide a team of engineers, fostering a culture of technical excellence and continuous learning.
Develop and maintain ROS‑based infrastructure for real‑time planning and execution.
Research and prototype cutting‑edge techniques such as Model Predictive Control, Monte Carlo Tree Search, Reinforcement Learning, and Hybrid A* planning.
Define and enforce best practices for code quality, documentation, and automated testing.
Partner with product management to translate customer requirements into technical specifications and deliverables.

Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, Robotics, or a related field.
7+ years of professional experience in motion planning, path planning, or related domains.
Strong proficiency in C++ programming (C++14/17) and modern software development practices.
Deep understanding of convex and nonlinear optimization, numerical methods, and control theory.
Hands‑on experience with ROS (Robot Operating System) and simulation tools.
Proven ability to lead technical teams and deliver complex projects on schedule.
Excellent problem‑solving skills with a data‑driven debugging mindset.
Effective communication skills for cross‑functional collaboration and stakeholder presentations.

Behavior planning, hybrid A* planning, and search‑based planning.
Model Predictive Control (MPC) and nonlinear control techniques.
Monte Carlo Tree Search (MCTS) and reinforcement learning applications in robotics.
Trajectory optimization, speed planning, and motion planning pipelines.
Convex optimization libraries (e.g., CPLEX, Gurobi, OSQP) and numerical optimization frameworks.
Experience with large‑scale simulation testing and validation environments.
System architecture design for autonomous vehicle platforms.
Cross‑functional collaboration with perception, mapping, and hardware teams.
Team leadership experience, including mentoring junior engineers.