Autonomous Driving Data Infrastructure Engineer

Xpeng Inc.; Santa Clara (CA); On-site; USD 175,000 - 296,000; Full time

Benefits offered by this job

Competitive compensation package

Snacks, lunches and fun activities

Job summary

XPENG is seeking a Data Infrastructure Engineer to analyze large autonomous driving datasets, identify edge cases impacting safety and comfort, and resolve them with in-house tools. You will collaborate with ML Engineers and the Annotation Team to apply data-centric AI principles.

Responsibilities include building scalable data lake/warehouse infrastructure, managing data quality, schemas, metadata, access controls, and performance. Proficiency in SQL, Python, and cloud storage is expected.

Qualifications

• BS in Computer Science or related field.
• 3+ years industrial experience.
• Fluent in English and Mandarin.
• Experience with data lakes, data warehouses and ETL/ELT pipelines.
• Familiar with data modeling and schema design.
• Knowledge of workflow orchestration and data quality management.

Responsibilities

• Identify edge cases in autonomous driving functionality by analyzing large field datasets.
• Resolve edge cases using in-house tools and collaborate with ML Engineers and Annotation Team.
• Monitor efficiency metrics and root causes to improve the edge-case resolution process.
• Build and maintain scalable data lake and data warehouse infrastructure for ingestion, storage, processing and analytics.

Skills

English & Mandarin

Python

SQL

Data Lakes

Data Warehouses

ETL/ELT

Data Modeling

Workflow Orchestration

Education

BS in Computer Science

Tools

Python

SQL

ETL Tools

Cloud Storage

Job description

XPENG is seeking a Data Infrastructure Engineer to analyze large autonomous driving datasets, identify edge cases impacting safety and comfort, and resolve them with in-house tools. You will collaborate with ML Engineers and the Annotation Team to apply data-centric AI principles.

Responsibilities include building scalable data lake/warehouse infrastructure, managing data quality, schemas, metadata, access controls, and performance. Proficiency in SQL, Python, and cloud storage is expected.