AI Engineer — Foundation Models & Auto-Labeling for Autonomous 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, Vin. Fast 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 an AI Engineer specializing in Foundation Models and Computer Vision to develop scalable auto-labeling solutions for autonomous-driving data. You will leverage Vision Foundation Models (VFMs), Vision-Language Models (VLMs), and multimodal AI to automatically generate high-quality annotations from large-scale driving datasets, reducing manual labeling effort and accelerating perception-model development.

Key Responsibilities

Develop foundation-model-based auto-labeling pipelines for 2D/3D detection, segmentation, tracking, lanes, freespace, traffic signs/lights, and scene understanding. Adapt and fine-tune VFMs/VLMs and multimodal models for autonomous-driving domains using fine-tuning, prompting, distillation, and pseudo-labeling. Leverage temporal and multimodal information to improve label accuracy and consistency across driving sequences.

Optimize foundation-model inference for large-scale, cost-efficient GPU processing and production deployment. Collaborate with perception, data, infrastructure, and annotation teams to integrate auto-labeling into the autonomous-driving data pipeline.

Requirements

BS/MS/PhD in Computer Science, AI, Robotics, Electrical Engineering, or related field. Strong expertise in Computer Vision, Deep Learning, and Foundation Models. Experience with Vision Transformers, VLMs, multimodal models, or self-supervised learning. Solid knowledge of object detection, segmentation, tracking, and 2D/3D perception.

Strong experience with Python, Py. Torch, and GPU-based model training/inference. Experience with large-scale datasets, model evaluation, and ML pipelines. Preferred: Experience with autonomous driving/ADAS, SAM-family models, DINO/Grounding DINO, CLIP/SigLIP-style models, open-vocabulary perception, BEV/3D perception, active learning, model distillation, TensorRT/ONNX, or distributed GPU inference.

Benefits

Opportunity to work on cutting-edge perception systems with real-world impact. A collaborative, fast-paced, and innovation-driven environment. Clear career growth path, leadership opportunities, and support for research and learning.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...

Work Location: In Ha Noi: Technopark Tower, Gia Lam, Ha Noi With respect to all your personal data shared to Vin. Fast in the application and the entire recruitment process of Vin. Fast, by clicking “Apply”, submitting your resumé/CV and/or participating in Vin. Fast's recruitment process, you agree that you have read Vin.

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