BCSC

Highly experienced AI & Autonomous Driving Engineer specializing in Londecision and trajectorymaking algorithms for autonomous driving especially for mapless. Expertise in planning control and optimization techniques such as MPC/LQR/QP POMDP Monte Carlo Tree Search (MCTS) Reinforcement Learning (RL) and AIbased search methods. Strong background in multithreaded C development numerical optimization and embedded systems. Passionate about developing robust and efficient decisionmaking algorithms to advance L2 autonomy.

1. Design and implement decision planning algorithms on mapless for lon decision and lon trajectory calculation aimed to have a algothrimbased method to solve lon problems especially for mergingintersectionopen space environment.
2. Collaborate closely with crossfunctional teams to seamlessly integrate decision planning and trajectory algorithms into the overall autonomous driving system architecture.
3. Analyze and address realworld challenges related to L2 autonomy including noisy input unstable prediction multiple predictions with best result for the current frame and a stable/robust interactive decision.
4. Continuously optimize and enhance gaming algorithmsoptimization lon trajectory to improve overall system efficiency adaptability and reliability.
5. Participate in project planning milestone setting and progress tracking to ensure timely delivery of autonomous driving features for mass production.
6. Ability and selfawareness to read and reproduce papers to solve complex problems.

Qualifications :

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• Masters degree or above in computer science electronic engineering mathematics or related fields.
• Senior AI & Autonomous Driving Engineer with expertise in decisionmaking algorithms for lon decision specializing in POMDP MCTS Tree searchgraph search.
• Strong background in C multithreading embedded system. Familiarity with A* Search Dynamic Programming (DP) Game Theory for MultiAgent Systems and Graph search/Tree search
• Need to have a deep think of the lon trajectory planning especially for systemlevel KPI and Subsystem KPI.
• Familiarity with numerical Optimization Principles and Engineering Implementation e.g. such as Graph Search Tree Search
• Proficiency in programming languages such as C Python etc. with strong coding skills for algorithm development and implementation.

Remote Work :

No

Employment Type :

Fulltime