Machine Learning Engineer, Foundation Model
About The Position
The Foundation Model Team focuses on building large-scale foundation models for multi-agent behavior prediction and autonomous vehicle planning . By leveraging DiDi Voyager’s unparalleled driving data, we train highly robust and generalizable deep learning systems that enable safe and intelligent autonomous driving at scale. Our models serve as the core intelligence of the autonomous driving stack, enabling vehicles to understand complex traffic scenarios, anticipate agent behavior, and make safe and efficient driving decisions. We operate at the intersection of large-scale machine learning, autonomous driving, and foundation model research , pushing the frontier of multi-agent prediction and planning.
Requirements
- Strong background in machine learning, deep learning, or robotics
- Experience with PyTorch / JAX / TensorFlow
- Solid understanding of modern neural architectures (transformers, diffusion, auto-regressive)
- Strong coding skills in Python and C++
- Passion for building real-world, safety-critical AI systems
Nice To Haves
- BS, MS or PhD in Computer Science, Machine Learning, Robotics, or a related field
- Experience in autonomous driving, robotics, or embodied AI
- Experience training large models on distributed GPU clusters
- Experience with trajectory prediction, planning, or decision-making systems
- Publications in top ML / robotics conferences (NeurIPS, ICML, ICLR, CVPR, RSS, CoRL, etc.)
Responsibilities
- Design and train large-scale deep learning models for: Multi-agent trajectory prediction Behavior and intent prediction Planning and decision-making
- Build foundation model architectures (Transformers, Diffusion, Flow-based models, Decision models, VLM/VLA)
- Develop scalable training pipelines across hundreds to thousands of GPUs
- Work with massive real-world datasets and build high-quality data pipelines
- Optimize models for latency, reliability, and on-vehicle deployment
- Collaborate closely with perception, mapping, simulation, and systems teams
- Drive research ideas into production systems used by real autonomous vehicles
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
