- Salary
- $126k – $213k
- Location
- Santa Clara, CA · Mountain View, California, United States
- Department
- General Intelligence Center
- Seniority
- Senior
- Education
- Master
- Source
- Greenhouse
Description
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.
As a Staff Technical Program Manager focused on the Autonomous Driving Training Data Lake, you will lead cross-functional programs that enable large-scale data collection, processing, governance, and delivery for autonomous-driving model development. You will work closely with data infrastructure, machine learning, simulation, vehicle engineering, annotation, and algorithm teams to ensure that high-quality training data is available reliably, efficiently, and at scale.
You will work with best-in-class machine learning, software, data, and infrastructure engineers to build the foundation for XPENG’s autonomous-driving development lifecycle. Your work will directly improve the quality, velocity, reliability, and cost efficiency of the data used to train and validate mass-market autonomous-driving systems.
Job Responsibilities:
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Define and manage the roadmap for the autonomous-driving training data lake, covering data collection, ingestion, processing, storage, curation, and delivery.
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Coordinate execution across data infrastructure, machine learning, annotation, simulation, and autonomous-driving algorithm teams.
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Establish and track KPIs for data quality, pipeline reliability, processing latency, dataset readiness, storage efficiency, and infrastructure cost.
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Drive programs for dataset generation, versioning, metadata management, lineage, and reproducibility.
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Identify technical risks and bottlenecks in data pipelines, infrastructure capacity, and training-data delivery, and lead cross-functional resolution.
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Improve engineering planning, agile development practices, dependency management, and operational processes across data platform teams.
Basic Qualifications:
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Bachelors or Masters in computer science or other related engineering field.
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5 years + of technical program management experience in engineering or related fields.
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Experience leading complex cross-functional data, infrastructure, software, or machine learning programs.
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Strong understanding of large-scale data systems, cloud infrastructure, and data pipelines.
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Mandarin speaking is required.
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Excellent problem-solving skills.
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Strong understanding of large-scale data systems, cloud infrastructure, and data pipelines.
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Experience in establishing strong software development processes.
Preferred Qualifications:
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Experience with autonomous-driving data platforms, machine learning infrastructure, or large-scale training-data systems.
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Experience managing large-scale data lakes, distributed data pipelines, or cloud infrastructure programs.
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Familiarity with data technologies such as object storage, Spark, Ray, Kafka, Iceberg, Parquet, Kubernetes, or similar systems.
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Understanding of machine learning data workflows, including data curation, annotation, training, evaluation, and closed-loop improvement.
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Experience managing complex cross-functional programs across multiple teams, locations, or time zones.
What do we provide:
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A fun, supportive and engaging environment.
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Opportunity to make a significant impact on the transportation revolution by the means of advancing autonomous driving.
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Opportunity to work on cutting edge technologies with the top talent in the field.
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Competitive compensation package.
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Snacks, lunches, dinners and fun activities.
The base salary range for this full-time position is $125,580 - $212,520, in addition to bonus, equity and benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training.
We are an Equal Opportunity Employer. It is our policy to provide equal employment opportunities to all qualified persons without regard to race, age, color, sex, sexual orientation, religion, national origin, disability, veteran status or marital status or any other prescribed category set forth in federal or state regulations.
Skills
KubernetesMachine LearningSparkProgram Management
