XPENG · 3 weeks ago
Senior Machine Learning Engineer – Perception/ End-to-End
XPENG is a leading smart technology company at the forefront of innovation, integrating advanced AI and autonomous driving technologies into its vehicles. They are seeking a Senior Machine Learning Engineer to research, implement, and evaluate deep learning algorithms for autonomous vehicle systems, collaborating with a team of experts in AI and software engineering.
Responsibilities
Research and develop cutting-edge deep learning algorithms for a unified, end-to-end onboard model that seamlessly integrates perception, prediction, and planning, replacing traditional modular model pipelines
Research and develop Vision-Language-Action (VLA) models to enable context-aware, multimodal decision-making, allowing the model to understand visual, textual, and action-based cues for enhanced driving intelligence
Address real-world challenges by enhancing online mapping, occupancy grid, and 3D detection models. Have deep expertise in perception systems and demonstrate strong problem-solving skills in analyzing and resolving production-level corner cases
Design and optimize highly efficient neural network architectures, ensuring they achieve low-latency, real-time execution on the vehicle’s high-performance computing platform, balancing accuracy, efficiency, and robustness
Develop and scale an offline machine learning (ML) infrastructure to support rapid adaptation, large-scale training, and continuous self-improvement of end-to-end models, leveraging self-supervised learning, imitation learning, and reinforcement learning
Deliver production-quality onboard software, working closely with sensor fusion, mapping, and perception teams to build the industry’s most intelligent and adaptive autonomous driving system
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 to rigorously benchmark model performance and generalization
Collaborate with system software engineers to deploy high-performance deep learning models on embedded automotive hardware, ensuring real-world robustness and reliability under diverse driving conditions
Work cross-functionally with AI researchers, computer vision experts, and autonomous driving engineers to push the frontier of end-to-end learning, leveraging advances in transformer-based architectures, diffusion models, and reinforcement learning to redefine the future of autonomous mobility
Qualification
Required
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
1-3 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
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
Benefits
Bonus
Equity
Benefits
Company
XPENG
XPeng is a leading Chinese Smart EV company that designs, develops, manufactures, and markets Smart EVs that appeal to the large and growing base of technology-savvy middle-class consumers.
Funding
Current Stage
Public CompanyTotal Funding
$7.8BKey Investors
China CITIC BankVolkswagen GroupAgricultural Bank of China
2025-08-18Post Ipo Debt· $1.39B
2023-07-26Post Ipo Equity· $700M
2022-04-27Post Ipo Debt· $1.14B
Recent News
2025-12-17
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