Senior Machine Learning Engineer - AI Foundation

XPENG is a leading smart technology company at the forefront of innovation, integrating advanced AI and autonomous driving technologies into its vehicles, including electric vehicles (EVs), electric vertical take-off and landing (eVTOL) aircraft, and robotics. With a strong focus on intelligent mobility, XPENG is dedicated to reshaping the future of transportation through cutting-edge R&D in AI, machine learning, and smart connectivity.

We are looking for a full-time Machine Learning Engineer - AI Foundation, with deep knowledge and strong enthusiasm towards establishing a state-of-art ML infrastructure for training very large foundation model and accelerating model training/inference.

Our mission is to solve the autonomous driving problem. You will work with a team of talented software engineers, machine learning engineers and research scientists to push the boundary of state-of-art machine learning models which will enable the next-generation E2E solution of autonomous driving.

Job Responsibilities:

• Design and implement training data pipeline that streams data from hundreds of petabytes of labeled and unlabeled data from a fleet of over a million vehicles.

• 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.

Minimum Skill Requirements:

• 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.

• Experience of performing large scale distributed training of models.

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