AI Foundation ML Engineer – Massive Training & Inference

XPENG; Santa Clara (CA); On-site; USD 175,000 - 296,000; Full time

Benefits offered by this job

Snacks

Lunches

Dinners

Fun activities

Job summary

XPENG is seeking a full-time Machine Learning Engineer - AI Foundation to build state-of-the-art ML infrastructure for training very large foundation models and speeding training/inference.

You will join a team of engineers and researchers focused on advancing autonomous driving through AI at scale, including data pipelines, training frameworks, and cloud inference for simulation and enterprise LLM/VLM applications.

Qualifications

• Master's degree in CS/CE/EE or equivalent.
• Deep knowledge of PyTorch.
• Knowledge of model inference framework (e.g. vLLM, SGLang).
• In-depth knowledge of transformer architecture and acceleration techniques.
• Experience with large-scale distributed training.

Responsibilities

• Design and implement training data pipeline from hundreds of petabytes of data across a fleet of vehicles.
• Implement training framework for physical AI foundation models (VLA 2.0, XWorld, Robotics).
• Accelerate training with state-of-the-art parallelisms (FSDP, Expert Parallel, Context Parallel, data types).
• Accelerate model inference on the cloud for simulation, RL, and enterprise LLM/VLM applications.

Skills

PyTorch

Transformer architecture

Distributed training

Profiling

Edge/accelerated inference

CUDA

Education

Master's Degree in CS/CE/EE

Tools

vLLM

SGLang

Job description

XPENG is seeking a full-time Machine Learning Engineer - AI Foundation to build state-of-the-art ML infrastructure for training very large foundation models and speeding training/inference.

You will join a team of engineers and researchers focused on advancing autonomous driving through AI at scale, including data pipelines, training frameworks, and cloud inference for simulation and enterprise LLM/VLM applications.