Expert or Senior Motion Prediction 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 looking for a Senior Motion Prediction Engineer with deep expertise in spatiotemporal modeling and machine learning to join our autonomous driving team. In this role, you will design, develop, and deploy advanced algorithms that predict the future trajectories of surrounding road users, including vehicles, cyclists, and pedestrians. Your work will directly influence planning and decision-making, enabling safe, efficient, and human-like driving behavior in complex traffic environments.

Requirements

• Develop state-of-the-art deep learning models for motion prediction in multi-agent, interactive driving scenarios

• Design and implement spatiotemporal architectures such as transformers, GNN , RNNs, or diffusion models for trajectory forecasting

• Fuse multi-modal perception outputs from camera, LiDAR and radar sensors into robust prediction pipelines

• Build interaction-aware and scene-context models that account for traffic rules and social behaviors

• Optimize prediction models for real-time performance on automotive embedded platforms

• Validate and benchmark models against large-scale datasets and diverse simulation scenarios

• Collaborate closely with perception , mapping, planning, and other teams to ensure seamless integration into the autonomous driving stack

• Contribute to dataset curation, annotation strategies, and scenario design for motion prediction tasks

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

• Strong foundation in machine learning and deep learning, with emphasis on spatiotemporal modeling and trajectory forecasting

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

• Hands-on experience with motion prediction models (Transformers, LSTM, GNN etc. )

• Familiarity with multi-modal sensor fusion and tracking systems

• Solid understanding of vehicle dynamics, traffic flow modeling, and interaction-aware prediction

• Experience optimizing and deploying models for real-time inference on embedded systems