Responsibilities:

· Design, prototype, test, and deploy state-of-the-art behavior planning algorithms for autonomous and assisted driving features.

· Develop and implement decision-making, trajectory and route planning, and optimization-based planning frameworks.

· Collaborate closely with perception, controls, localization, and systems teams to ensure robust and efficient integration of planning software.

· Drive innovation through the invention of novel algorithms and features that elevate the safety, comfort, and intelligence of Lucid vehicles.

· Support the validation and verification of behavior planning components in simulation, hardware-in-the-loop (HIL), and on-road testing environments.

Required Qualifications:

· MS degree in Robotics, Computer Science, Aerospace Engineering, Mechanical Engineering, or a related field (or equivalent experience).

· 2+ years of professional experience, or a Ph.D. in a relevant discipline.

· Strong C++ programming skills with a solid understanding of software engineering best practices.

· Deep knowledge of decision-making algorithms such as graph/tree search methods or AI-based planners.

· Experience with motion and behavior planning concepts including decision-making under uncertainty, optimization techniques, trajectory generation, and route planning.

· Hands-on experience with embedded systems integration in robotics or automotive domains.

· Strong communication and problem-solving skills.

Preferred Qualifications:

· Experience with middleware systems such as ROS or DDS.

· Proficiency in scripting languages such as Python, Bash.

· Experience with simulation tools (e.g., Gazebo, CARLA) and frameworks for testing autonomous systems.

· Experience and understanding of deep learning frameworks (e.g., TensorFlow, PyTorch).

· Experience and knowledge of imitation/reinforcement learning techniques.

· Familiarity with version control systems (e.g., Git) and modern development workflows.

· Prior work on scenario-based testing, MIL/SIL/HIL environments, or automated test frameworks.

· Exposure to CI tools such as Jenkins or GitLab CI.