XPENG & Volkswagen Group
Senior Computer Vision Engineer - Deployment
XPENG & Volkswagen Group, Santa Clara, California, us, 95053
XPENG Overview
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), eVTOL aircraft, and robotics. The company focuses on reshaping the future of transportation through cutting-edge R&D in AI, machine learning, and smart connectivity. Position
Senior Computer Vision Engineer
to lead the development and deployment of high-performance, large-scale AI models. You will focus on optimizing model inference, implementing compression techniques (quantization, pruning, distillation), and ensuring efficient on-device deployment across GPU and custom AI accelerator platforms. Your work will directly enable the next generation of intelligent systems in autonomous driving and beyond. Responsibilities
Optimize large-scale multimodal models for low-latency inference and efficient memory usage across diverse hardware platforms. Apply state-of-the-art model compression techniques, including quantization (e.g., INT8/FP16), pruning, and knowledge distillation. Develop and integrate custom inference kernels targeting GPU or custom AI accelerators. Build profiling tools and performance models to analyze bottlenecks and guide optimization strategies. Contribute to real-world deployment efforts in autonomous driving systems, including on-vehicle testing and iteration. Track the latest research in efficient ML inference and integrate relevant techniques into production pipelines. Qualifications
Master’s or Ph.D. in Computer Science, Electrical Engineering, or related field. Open to recent graduates. Strong coding skills in C++ and Python with a focus on performance and scalability. Proficient in deploying deep learning models using TensorRT, ONNX Runtime, or TVM. Familiarity with CUDA programming and parallel computing principles. Solid understanding of model inference workflows and system-level performance tuning. Effective communicator and collaborative team player. Preferred Qualifications
Hands-on experience with deploying vision-language or large multimodal models. Familiarity with low-precision inference (INT8/FP16), kernel fusion, and operator-level optimization. Experience in autonomous driving, robotics, or edge AI applications. Track record of open-source contributions or publications in ML/AI conferences (e.g., NeurIPS, ICML, CVPR). Background in system profiling, latency modeling, or compiler-level optimization. What We Provide
A fun, supportive and engaging environment. Infrastructures and computational resources to support your work. Opportunity to work on cutting-edge technologies with top talents in the field. Opportunity to make a significant impact on the transportation revolution through advancing autonomous driving. Competitive compensation package. Snacks, lunches, dinners, and team activities. The base salary range for this full-time position is $174,720 - $295,680, plus bonus, equity and benefits. Salary ranges are determined by role, level, and location, and the posted range reflects minimum and maximum targets for new hires across US locations. Equal Opportunity
We are an Equal Opportunity Employer. It is our policy to provide equal employment opportunities to all qualified persons regardless of race, age, color, sex, sexual orientation, religion, national origin, disability, veteran status, marital status, or any other category protected by law.
#J-18808-Ljbffr
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), eVTOL aircraft, and robotics. The company focuses on reshaping the future of transportation through cutting-edge R&D in AI, machine learning, and smart connectivity. Position
Senior Computer Vision Engineer
to lead the development and deployment of high-performance, large-scale AI models. You will focus on optimizing model inference, implementing compression techniques (quantization, pruning, distillation), and ensuring efficient on-device deployment across GPU and custom AI accelerator platforms. Your work will directly enable the next generation of intelligent systems in autonomous driving and beyond. Responsibilities
Optimize large-scale multimodal models for low-latency inference and efficient memory usage across diverse hardware platforms. Apply state-of-the-art model compression techniques, including quantization (e.g., INT8/FP16), pruning, and knowledge distillation. Develop and integrate custom inference kernels targeting GPU or custom AI accelerators. Build profiling tools and performance models to analyze bottlenecks and guide optimization strategies. Contribute to real-world deployment efforts in autonomous driving systems, including on-vehicle testing and iteration. Track the latest research in efficient ML inference and integrate relevant techniques into production pipelines. Qualifications
Master’s or Ph.D. in Computer Science, Electrical Engineering, or related field. Open to recent graduates. Strong coding skills in C++ and Python with a focus on performance and scalability. Proficient in deploying deep learning models using TensorRT, ONNX Runtime, or TVM. Familiarity with CUDA programming and parallel computing principles. Solid understanding of model inference workflows and system-level performance tuning. Effective communicator and collaborative team player. Preferred Qualifications
Hands-on experience with deploying vision-language or large multimodal models. Familiarity with low-precision inference (INT8/FP16), kernel fusion, and operator-level optimization. Experience in autonomous driving, robotics, or edge AI applications. Track record of open-source contributions or publications in ML/AI conferences (e.g., NeurIPS, ICML, CVPR). Background in system profiling, latency modeling, or compiler-level optimization. What We Provide
A fun, supportive and engaging environment. Infrastructures and computational resources to support your work. Opportunity to work on cutting-edge technologies with top talents in the field. Opportunity to make a significant impact on the transportation revolution through advancing autonomous driving. Competitive compensation package. Snacks, lunches, dinners, and team activities. The base salary range for this full-time position is $174,720 - $295,680, plus bonus, equity and benefits. Salary ranges are determined by role, level, and location, and the posted range reflects minimum and maximum targets for new hires across US locations. Equal Opportunity
We are an Equal Opportunity Employer. It is our policy to provide equal employment opportunities to all qualified persons regardless of race, age, color, sex, sexual orientation, religion, national origin, disability, veteran status, marital status, or any other category protected by law.
#J-18808-Ljbffr