Staff 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:

• Optimize transformer-based LLMs for low-latency and high-throughput inference.

• Optimize kernels and model graphs using tools like CUDA, Triton, and custom fused operators.

• Implement and benchmark (Quantization, Knowledge distillation, structured and unstructured pruning, KV-cache optimization, etc.).

• Deploy optimized models across GPUs, CPUs, and edge acceleators.

• Contribute to internal tooling and documentation for model optimization flows.

Minimum Skill Requirements:

• Master in CS/CE/EE, or equivalent, with 5-8 years of industry experience.

• Good knowledge of PyTorch.

• Knowledge of transformer architecture and ways to accelerate the training and inference of transformer models.

Preferred Skill Requirements:

• Previous experience in the autonomous driving industry.

• Knowledge of Torchscript and Nvidia TensorRT.

• Strong programming skills in Python and C++

• Familiarity with GPU CPU, NPU, DSP architecture.

• Deep understanding of memory bandwidth, compute bottlenecks, and hardware-aware model optimization

• Being efficiently in solving complex problems collaboratively on larger teams

What do we provide:

• 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 significant impact on the transportation revolution by the means of advancing autonomous driving.
• Competitive compensation package.
• Snacks, lunches, dinners, and fun activities.

The base salary range for this full-time position is $215,280 - $364,320, in addition to bonus,