Senior Machine Learning Engineer - AI Foundation
$174.72k - $295.68kFull-time
XPENG
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.
- Master in CS/CE/EE, or equivalent, with 3 + years of industry experience.
- Good knowledge of PyTorch.
- Knowledge of transformer architecture and ways to accelerate the training and inference of transformer models.
- 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
- 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.
Vacancy posted 25 days ago
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