XPENG Deutschland
Senior Staff Machine Learning Engineer – Perception/ End-to-End
XPENG Deutschland, Santa Clara, California, us, 95053
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Senior Staff Machine Learning Engineer – Perception/ End-to-End
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XPENG XPENG
is a leading smart technology company at the forefront of innovation, integrating advanced AI and autonomous driving technologies into its vehicles. We are seeking Deep Learning Engineers with strong expertise in machine learning and deep learning system design, along with solid software development skills. In this role, you will research, implement, and evaluate a unified end-to-end onboard model leveraging state-of-the-art technologies. You will collaborate with a world-class team of experts in computer vision, AI systems, and software engineering to push the boundaries of autonomous vehicle performance. Job Responsibilities Research and develop cutting-edge deep learning algorithms for a unified, end-to-end onboard model. Research and develop Vision-Language-Action (VLA) models to enable context-aware, multimodal decision-making. Address real-world challenges by enhancing online mapping, occupancy grid, and 3D detection models. Design and optimize highly efficient neural network architectures, ensuring low-latency, real-time execution. Develop and scale an offline machine learning infrastructure to support rapid adaptation, large-scale training, and continuous self-improvement of end-to-end models. Deliver production-quality onboard software, working closely with sensor fusion, mapping, and perception teams. Leverage massive real-world datasets collected from our autonomous fleet, integrating multi-modal sensor data to train and refine state-of-the-art end-to-end driving models. Design, conduct, and analyze large-scale experiments, including sim-to-real transfer, closed-loop evaluation, and real-world testing. Collaborate with system software engineers to deploy high-performance deep learning models on embedded automotive hardware. Work cross-functionally with AI researchers, computer vision experts, and autonomous driving engineers to push the frontier of end-to-end learning. Minimum Skill Requirements MS or PhD level education in Engineering or Computer Science with a focus on Deep Learning, Artificial Intelligence, or a related field, or equivalent experience. Strong experience in applied deep learning including model architecture design, model training, data mining, and data analytics. 5-7 years + of experience working with DL frameworks such as PyTorch, Tensorflow. Strong Python programming experience with software design skills. Solid understanding of data structures, algorithms, code optimization, and large-scale data processing. Excellent problem-solving skills. Preferred Skill Requirements Hands-on experience in developing DL-based planning engine for autonomous driving. Experience in applying CNN/RNN/GNN, attention model, or time series analysis to real-world problems. Experience in other ML/DL applications, e.g., reinforcement learning. Experience in DL model deployment and optimization tools such as ONNX and TensorRT. The base salary range for this full-time position is $244,140-$413,160, in addition to bonus, equity, and benefits. We are an Equal Opportunity Employer.
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Senior Staff Machine Learning Engineer – Perception/ End-to-End
role at
XPENG XPENG
is a leading smart technology company at the forefront of innovation, integrating advanced AI and autonomous driving technologies into its vehicles. We are seeking Deep Learning Engineers with strong expertise in machine learning and deep learning system design, along with solid software development skills. In this role, you will research, implement, and evaluate a unified end-to-end onboard model leveraging state-of-the-art technologies. You will collaborate with a world-class team of experts in computer vision, AI systems, and software engineering to push the boundaries of autonomous vehicle performance. Job Responsibilities Research and develop cutting-edge deep learning algorithms for a unified, end-to-end onboard model. Research and develop Vision-Language-Action (VLA) models to enable context-aware, multimodal decision-making. Address real-world challenges by enhancing online mapping, occupancy grid, and 3D detection models. Design and optimize highly efficient neural network architectures, ensuring low-latency, real-time execution. Develop and scale an offline machine learning infrastructure to support rapid adaptation, large-scale training, and continuous self-improvement of end-to-end models. Deliver production-quality onboard software, working closely with sensor fusion, mapping, and perception teams. Leverage massive real-world datasets collected from our autonomous fleet, integrating multi-modal sensor data to train and refine state-of-the-art end-to-end driving models. Design, conduct, and analyze large-scale experiments, including sim-to-real transfer, closed-loop evaluation, and real-world testing. Collaborate with system software engineers to deploy high-performance deep learning models on embedded automotive hardware. Work cross-functionally with AI researchers, computer vision experts, and autonomous driving engineers to push the frontier of end-to-end learning. Minimum Skill Requirements MS or PhD level education in Engineering or Computer Science with a focus on Deep Learning, Artificial Intelligence, or a related field, or equivalent experience. Strong experience in applied deep learning including model architecture design, model training, data mining, and data analytics. 5-7 years + of experience working with DL frameworks such as PyTorch, Tensorflow. Strong Python programming experience with software design skills. Solid understanding of data structures, algorithms, code optimization, and large-scale data processing. Excellent problem-solving skills. Preferred Skill Requirements Hands-on experience in developing DL-based planning engine for autonomous driving. Experience in applying CNN/RNN/GNN, attention model, or time series analysis to real-world problems. Experience in other ML/DL applications, e.g., reinforcement learning. Experience in DL model deployment and optimization tools such as ONNX and TensorRT. The base salary range for this full-time position is $244,140-$413,160, in addition to bonus, equity, and benefits. We are an Equal Opportunity Employer.
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