Senior Engineer, Navigation (Prediction, Decision and Planning)

Job Description:

• Experiences on object trajectory/intention prediction, decision making and motion planning, to help ensure that the smart vehicles solutions are smart enough and perform at the highest levels.
• Develop and verify algorithm across a real Smart Driving and Autonomous Vehicle system of software and hardware.
• Design and implement motion prediction, decision making and motion planning solution for self-driving vehicle
• Driving scenario analysis, Software-In-the-Loop simulation, behaviour/strategy design and motion planning.
• Algorithm implementation and software validation
• On-road performance verification
• Code review
• Write professional design and technical documents

Job Requirements:

• Master or Bachelor Degree in Computer Science, Robotics, Control System or related engineering field
• Good programming skill on C++, with 3+ years software development professional experience
• Good knowledge on robotics decision system, e.g., Finite State Machine, Behaviour Tree, Expert System, POMDP etc.
• Familiar with path planning algorithms, e.g., A*, D*, RRT etc.
• Familiar with common DNN methods, understand typical network training process, and experience on at least one deep learning framework (pytorch/caffe/tensorflow)
• Good knowledge on Imitation Learning, Reinforcement Learning, and their applications on real-time system
• Familiar with Computational Geometry, Vehicle Kinematics and Dynamics
• Development experience on Linux OS environment
• Practical development experience on Robotics Operating System (ROS)
• Practical development experience on Robotics/Autonomous Vehicle will be a Plus.

The above information on this description has been designed to indicate the general nature, and level, of the work performed by this position. It is not designed to contain, or be interpreted, as a comprehensive inventory of all duties, responsibilities and qualifications required.

Interested candidates may also apply or write in to CS Chua, EA 12C6130/ R1548619 [email protected]. Shortlisted candidates will be contacted for a discussion.