Expert Motion Planning Engineer - Self-Driving

VINFAST is a pioneering electric vehicle (EV) company committed to revolutionizing the automotive industry with sustainable and innovative mobility solutions. As a leading player in the EV market, VinFast is dedicated to delivering high-quality, cutting-edge electric vehicles that redefine the driving experience. Our team consists of passionate professionals driven by a shared vision of creating a greener and more sustainable future through innovation, technology, and excellence. 

• Design, develop, and optimize motion planning algorithms that handle complex, interactive traffic scenarios 
  

• Formulate and implement trajectory generation methods that balance safety, comfort, and efficiency under real-world driving conditions 
  

• Research and apply state-of-the-art planning methods, including optimization-based approaches, probabilistic decision-making, reinforcement learning, and imitation learning 
  

• Integrate perception, prediction, and mapping outputs into planning pipelines for robust decision-making 
  

• Ensure real-time performance of planning algorithms on automotive-grade embedded hardware 
  

• Contribute to the development of closed-loop validation pipelines, including simulation, software-in-the-loop, hardware-in-the-loop, and on-road vehicle testing 
  

• Collaborate with multidisciplinary teams (perception, prediction, map generation, controls, systems) to integrate planning algorithms into the self-driving autonomy stack 
  

• Stay current with advances in motion planning, decision-making, and learning-based approaches for autonomous driving 
  

• Drive engineering excellence by writing clean, efficient, and well-tested code 
  

• MSc/PhD in Robotics, Computer Science, Electrical or Mechanical Engineering, or a related field with 5+ years of relevant industry experience 
  

• Strong background in motion planning, trajectory optimization, and decision-making methods (e.g., A*, optimization-based planning, graph search etc.) 
  

• Experience with reinforcement learning, imitation learning, or deep learning approaches for planning and control 
  

• Proficiency in Python and C++, with familiarity in ML frameworks such as PyTorch or TensorFlow 
  

• Solid understanding of vehicle dynamics, kinematics, and control theory 
  

• Hands-on experience with real-time systems, performance optimization, and deployment on embedded automotive hardware 
  

• Skilled in simulation-based development and validation using tools such as CARLA or MATLAB/Simulink 
  

• Strong mathematical foundation in optimization, linear algebra, probability, and statistics 
  

• Excellent problem-solving skills and ability to work in fast-paced, collaborative environments 
  

• Nice to have: Prior experience in self-driving or ADAS development and familiarity with functional safety standards (ISO 26262, SOTIF)