Expert Motion Planning Engineer - Self-Driving

Overview

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 looking for a Senior Motion Planning Engineer to design and implement the core algorithms that enable autonomous vehicles to make safe, efficient, and human-like driving decisions in dynamic and uncertain environments. In this role, you will work at the intersection of decision-making, trajectory generation, and control, collaborating closely with perception, prediction, map generation and controls teams to build a reliable, real-time motion planning system for self-driving.

Responsibilities

• 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

Qualifications

• 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
• Opportunity to collaborate with and learn from industry-leading professionals in the automotive domain.

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