Motion Planning & Control 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.

We are seeking a highly skilled Experts, Senior s, Engineers to join our self-driving team. In this role, you will design, develop, and deploy advanced algorithms that enable autonomous vehicles to accurately sense, interpret, and interact with the world around them. You will work on cutting-edge challenges in 3D object and occupancy detection, tracking, sensor fusion, scene understanding, and foundation models for self-driving, with direct impact on the safety and performance of our autonomous systems. This is an opportunity to contribute at the intersection of deep learning, computer vision, robotics, and system engineering, while collaborating with a world-class team of researchers and engineers.

• 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

Requirements

• 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)

Benefits

• Competitive salary Premium healthcare package, including PVI insurance & annual health check-ups
• 13th-month salary & performance bonuses to reward your contributions
• Enjoy preferential pricing for services within the Vingroup ecosystem including Vinmec, Vinpearl, and Vinschool...
• Opportunity to collaborate with and learn from industry-leading professionals in the automotive domain

Work Location:

• In Ha Noi: Technopark Tower, Gia Lam, Ha Noi
• In Ho Chi Minh: No. 25, Riverview 6, Vinhomes Golden River, 02 Ton Duc Thang Street, Ben Nghe Ward, District 1, Ho Chi Minh City

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