E2E PnC Expert_XC

Job Description for End-to-End PnC Expert: Design and implement end-to-end decision planning algorithms for L2++ autonomous driving systems, ensuring robust performance and safety in mass production. Collaborate closely with cross-functional teams to integrate decision planning algorithms seamlessly into the overall autonomous driving system architecture. Analyze and address real-world challenges for L2++ autonomy, such as dynamic road conditions, complex traffic scenarios, and environmental diversity, all without relying on HD maps. Continuously optimize and enhance decision planning algorithms to improve system efficiency, adaptability, and reliability, from simulation to real-world deployment. Participate in project planning, setting milestones, and tracking progress to ensure the timely delivery of autonomous driving features for mass production. Stay updated on the latest advancements in autonomous driving technology and incorporate new insights and techniques into PnC algorithms to maintain cutting-edge performance.

Qualifications

A good candidate is prefer to:

Master’s degree or above in computer science, electronic engineering, mathematics, or related understanding and practical experience in PnC algorithms for autonomous driving systems, with experience at convex optimization MPC/iLQR/ understanding and practical experience for seaching / sampling / Optimization algorithm for path generation.Familiarity with AI Planner and experienced in safety check for model based planner output.Proficiency in programming languages such as C++, Python, etc., with strong coding skills for algorithm development and implementation.Excellent problem-solving skills and the ability to analyze complex technical issues related to autonomous driving.

Strong communication skills and a collaborative mindset, with the ability to work effectively in cross-functional teams

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