Role:

Develop and maintain software and algorithms enabling vehicles to complete parking maneuvers safely, accurately, and reliably Design reusable, optimized behavior and motion planning software architectures for Level 2/3/4 autonomous parking systems Construct and implement advanced machine learning algorithms for data-driven parking behavior Lead software development by leveraging stack architecture expertise to design and implement algorithms in real-world systems Develop high performance behavior and motion planning algorithms with low latency Design, prototype, test, and release cutting-edge planning software stacks for Lucid production programs Implement high-quality automotive grade software code compliant to automotive quality and safety standards Work closely with other teams to ensure a seamless and robust implementation and deployment of motion planning products for autonomous parking systems Maintain alignment through effective communication Support the production verification and validation of the motion planning algorithms using prototype vehicles and pre-production vehicles

Required Qualifications:

Bachelor's degree Computer Science, Robotics, ML or equivalent experience Professional experience implementing reliable production systems involving large-scale systems, evaluation pipelines, ML models and performance metrics Proficiency in C++ and hands-on SWE design skills Comfortable with fundamentals of physics, probability, and statistics Excellent communication skills and willingness to learn

Preferred Qualifications:

Masters or higher degree preferably in ML, robotics, or related field Experience in AV planning and behavior prediction Experience developing real-time systems Hands-on experience testing complex AV systems on real-world platforms