Apply

Ready to go for it?

AI Apply speeds things up—apply directly if you prefer.

FREE ACCESS
5,000–10,000 jobs/day
JobTailor Logo

See all jobs on JobTailor

Search thousands of fresh jobs every day.

Discover
  • Fresh listings
  • Fast filters
  • No subscription required
Create a free account and start exploring right away.
42dot

Senior AI Data Pipeline Engineer – Autonomous Driving

42dot

AI Data Pipeline Engineer developing reliable data extraction and labeling pipelines for autonomous driving technologies. Building infrastructure to support ML model training and deployment in cloud environments.

Posted 4/29/2026full-timeSunnyvale • California • 🇺🇸 United StatesSenior💰 $133,000 - $254,000 per yearWebsite

Tech Stack

Tools & technologies
AirflowApacheBootstrapCloudMongoDBPostgresPythonSpark

About the role

Key responsibilities & impact
  • Develop high scale, reliable data extraction pipeline to extract millions of raw data from data collection fleet and convert to high-value scene data
  • Develop data labeling pipelines to perform the auto labeling inferences for autonomous driving algorithms
  • Develop advanced autonomous driving data SDK, including scene data search, datasets preparation, dataset loading, etc.
  • Build up the data lakehouse for autonomous driving scene dataset, including the sensor data, calibration data, as well as annotation data
  • Dig into performance bottlenecks all along the data processing pipelines, from data processing latency, data search latency to Test Procedure (TP) coverage.
  • Bootstrap and maintain infrastructure for data platform components—data processing pipeline, database, data lakehouse and data serving.
  • Collaborate with cross-functional teams, including ML algorithm, ML application, and Cloud Infra to align data pipelines with overall autonomous driving system architecture.

Requirements

What you’ll need
  • Bachelor's degree or higher in Computer Science, Engineering, Robotics, or a similar technical field.
  • Minimum of 7 years of experience in Data Engineering, DataOps or ML Platform roles
  • Proficient in Python and solid experience in Python SDK development
  • Solid hands-on experience with data pipeline job orchestration with Databricks Workflows or Apache Airflow, as well as integrating data pipelines with machine learning models
  • Solid working experience in Databases (e.g., MongoDB, PostgreSQL, etc)
  • Extensive experience with data technologies and architectures such as Data Warehouse (e.g., Hive) or Lakehouse (e.g., Delta Lake)
  • Experience with Apache Spark or other big data computing engines
  • Excellent leadership and communication skills, with a demonstrated ability to lead technical projects.

Benefits

Comp & perks
  • Health insurance
  • 401(k)
  • Professional development opportunities
  • Flexible work arrangements
  • Bonuses

ATS Keywords

✓ Tailor your resume
Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools
Pythondata pipeline orchestrationDatabricks WorkflowsApache AirflowMongoDBPostgreSQLData WarehouseLakehouseApache Sparkdata extraction
Soft Skills
leadershipcommunication