AI Engineer — Foundation Models & Auto-Labeling for Autonomous Driving
Viet Nam·Hanoimid
Machine Learning EngineerData
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Quick Summary
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,
Technical Tools
Machine Learning EngineerData
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 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, PyTorch, 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 VinFast in the application and the entire recruitment process of VinFast, by clicking “Apply”, submitting your resumé/CV and/or participating in VinFast's recruitment process, you agree that you have read VinFast's Personal Data Protection Policy ("Policy") posted at https://vinfastauto.com/vn_vi/dieu-khoan-phap-ly or https://vinfast.vn/privacy-policy/, you agree to the Policy and consent for VinFast to process your personal data in accordance with the Policy and the applicable regulations on personal data protection. To all recruitment agencies: VinFast does not accept agency resumes. Please do not forward resumes to our careers alias or other VinFast employees. VinFast is not responsible for any fees related to unsolicited resumes.
Location & Eligibility
Where is the job
Hanoi, Viet Nam
On-site at the office
Listing Details
- Posted
- October 8, 2026
- First seen
- October 8, 2026
- Last seen
- October 8, 2026
Posting Health
- Days active
- -1
- Repost count
- 0
- Trust Level
- 57%
- Scored at
- October 8, 2026
Signal breakdown
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External application
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