Senior Machine Learning Engineer - AI Foundation

Design and implement training data pipeline that streams data from hundreds of petabytes of labeled and unlabeled data from a fleet of over a…

Implement training framework for all physical AI foundation models in XPeng, including VLA 2.0, XWorld, Robotics.

Accelerate training with state of the art parallelisms, e.g., FSDP, Expert Parallel, Context Parallel, and data types.

Accelerate model inference on the cloud for closed-loop simulation, reinforcement learning, and enterprise LLM/VLM applications.

Master's Degree in CS/CE/EE, or equivalent, in industry experience.

Deep knowledge of PyTorch.

Knowledge of model inference framework (e.g. vLLM, SGLang).

In-depth knowledge of transformer architecture and ways to accelerate the training and inference of transformer models.