Senior Machine Learning Engineer
Core
Design and implement training data pipelines at hundreds-of-petabytes scale from millions of vehicles; implement training frameworks for physical AI foundation models (VLA 2.0, XWorld, Robotics) and accelerate cloud model inference for simulation and enterprise LLM/VLM applications.
Role type
Senior IC machine learning engineer (autonomous driving)
Builds
Physical AI foundation models, training data pipelines, cloud inference systems for closed-loop simulation and enterprise LLM/VLM applications
Domain
Autonomous driving, large-scale distributed AI
Deliverable
production ML models
Required skills
PyTorch, transformer architecture, large-scale distributed model training, model profiling and performance optimization
Preferred skills
CUDA custom operations, edge computing systems, distributed computing frameworks (Ray), autonomous driving industry experience, model inference frameworks (vLLM, SGLang)
Technologies
PyTorch, vLLM, SGLang, FSDP, Expert Parallel, Context Parallel, CUDA, Ray
Responsibilities
Design and implement training data pipelines streaming labeled and unlabeled data at hundreds-of-petabytes scale; Implement training frameworks for XPENG physical AI foundation models; Accelerate model training using FSDP, Expert Parallel, Context Parallel, and advanced data types; Accelerate cloud model inference for closed-loop simulation, reinforcement learning, and enterprise LLM/VLM applications; Profile models and investigate performance bottlenecks to improve training and inference speed
Seniority
Senior, hands-on IC
