Senior Staff Physical AI Data Algorithm Engineer
XpengmotorsRole Overview
Xpengmotors is hiring a Senior Staff Physical AI Data Algorithm Engineer. This is a full-time role in Santa Clara. Full responsibilities, required qualifications, and the apply link are listed in the description below.
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Job description
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Responsible for the design and optimization of the vehicle-cloud integrated data closed-loop architecture: Build and maintain the full-link large closed-loop system from on-vehicle data upload to cloud training and simulation evaluation, ensuring efficient and secure data flow between the vehicle and the cloud to support rapid model iteration.
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Build and maintain the data closed-loop toolchain: Lead the selection, development and integration of modules such as data processing links, data mining, collection and annotation tools, and visualization tools to improve the automation level and processing efficiency of data from original collection to usable data sets.
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Establish data lineage and version management mechanisms: Design and implement a data lineage tracking system to achieve full-process traceability of data from production, processing to use; establish strict corresponding relationships between data sets, annotation versions, and model versions to support problem attribution and iterative backtracking.
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Explore the next-generation AI Agent-centric data closed-loop technology: Research and introduce AI Agent-based automated data processing and mining methods, explore the application of Agents in scenarios such as scene recognition, annotation assistance, and simulation use case generation, and promote the evolution of data closed-loop towards a higher level of intelligence.
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Support data work throughout the entire model development cycle: Deeply participate in the entire process of the model from data preparation, pre-training, fine-tuning, evaluation to on-board deployment and continuous optimization, understand the specific data needs of the model at each stage, and provide targeted data strategy support.
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Define high-quality data standards and guide data production: According to the key needs of different models at different stages (such as basic capability building, shortcoming repair, generalization improvement, etc.), clarify the characteristics of high-quality data (diversity, representativeness, scarcity, authenticity, etc.), guide data collection, cleaning and annotation work, and ensure model training effects.
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Master's degree or above in Computer Science, Artificial Intelligence, Automation, Vehicle Engineering or related majors, with more than 3 years of work experience in multi-modal physical AI or AI data platform. In-depth understanding of the architecture and process of multi-modal physical AI data closed-loop, with integrated practical experience in on-vehicle data upload, cloud data processing, training and simulation integration.
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Candidates with experience in large-scale AI training data governance are preferred, including the construction of data standard systems, data quality governance, data asset management, cost and efficiency optimization, as well as practical experience in the implementation of massive multi-modal data production and circulation systems.
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Familiar with the construction and use of data closed-loop toolchains, including data processing, mining, annotation, visualization and other modules, with relevant development or in-depth use experience.
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Have practical experience in the implementation of data lineage and version management, understand the importance of the association between data sets and model versions, and have a sense of data asset management.
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Have research or practical interest in the direction of AI Agent-centric data closed-loop, and have the ability to explore cutting-edge technologies.
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Familiar with the entire life cycle of model development, and deeply understand the key role of data in model performance (generalization, robustness, security).
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Able to analyze the data needs of the model at different stages, have the ability to define and evaluate high-quality data, and candidates with experience in guiding data production and annotation are preferred.
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Have good cross-team collaboration ability, able to work efficiently with algorithms, engineering, annotation, testing and other teams to promote the landing of data closed-loop.
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A fun, supportive and engaging environment.
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Infrastructures and computational resources to support your work.
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Opportunity to work on cutting edge technologies with the top talents in the field.
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Opportunity to make significant impact on the transportation revolution by the means of advancing autonomous driving.
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Competitive compensation package.
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Snacks, lunches, dinners, and fun activities.
About Xpengmotors
Xpengmotors
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Frequently Asked Questions
How do I apply for the Senior Staff Physical AI Data Algorithm Engineer position at Xpengmotors?
Use the Apply button above to submit your application directly to Xpengmotors. Most applications take less than 5 minutes if your resume and contact details are ready, and you'll be routed to the employer's official application system to finish.
Where is the Senior Staff Physical AI Data Algorithm Engineer position at Xpengmotors located?
This position is based in Santa Clara. Xpengmotors has not indicated remote or hybrid options for this role, so candidates should plan for on-site work.
What does a Senior Staff Physical AI Data Algorithm Engineer at Xpengmotors earn?
Xpengmotors has not disclosed a salary range in this posting. Many employers share specifics later in the interview process; you can also ask during a recruiter screen if compensation transparency is important to you.
When was the Senior Staff Physical AI Data Algorithm Engineer role at Xpengmotors posted?
This role was posted on June 1, 2026 (38 days ago). It's still listed as actively hiring; we re-confirm openings against the source system multiple times per day and remove closed roles.
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