Senior Machine Learning Engineer - AI Foundation

XPENGSanta Clara, CA
$174,720 - $295,680

About The Position

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.

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.
  • A track record of profiling model and doing detective work to improve model training and inference speed.

Nice To Haves

  • Previous experience in the autonomous driving industry.
  • Experience with CUDA language for writing custom ops.
  • Experience with edge computing systems.
  • Knowledge of disributed computing frameworks, such as Ray.
  • A track record of efficiently solving complex problems collaboratively on larger teams

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.

Benefits

  • A fun, supportive and engaging environment.
  • Infrastructures and computational resources to support your work.
  • Opportunity to work on cutting edge technologies with the top talents in the field.
  • Opportunity to make a significant impact on the transportation revolution by the means of advancing autonomous driving.
  • Competitive compensation package.
  • Snacks, lunches, dinners, and fun activities.
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