Back to jobs

Senior AI Data Pipeline Engineer (Autonomous Driving)

Sunnyvale, United States · San Francisco, Califonia, US

Pay
$133,000–254,000/yearAnnual period assumed — pay source
Compensation $133,000 - $254,000 Additional Information
Read the full posting
Work setting
Hybrid — work setting source
Location type: Hybrid
From the employer’s posting
Employment
Full-time — employment source
Employment type: Full-time
From the employer’s posting
Team
ENGINEERING › Autonomous Driving — team source
Department: ENGINEERING › Autonomous Driving
From the employer’s posting

Before you apply

Sponsorship
Visa sponsorship not confirmed — sponsorship source
2. Do you now, or will you in the future, require immigration sponsorship for work authorization (for example, H-1B status)?
From the employer’s application form
Apply at 42dot

What you’ll work on

Full posting
  • Build pipelines that extract millions of raw fleet records into scene data

  • Develop auto-labeling pipelines for autonomous driving algorithms

  • Build the autonomous driving data SDK for scene search and dataset loading

  • Build a data lakehouse for sensor, calibration and annotation data

  • Find and fix bottlenecks in processing, search and test coverage latency

From the employer’s posting
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

What you’ll bring

All qualifications

Core experience

  • Bachelor's degree or higher in Computer Science, Engineering, Robotics, or a similar technical field.
  • Proficient in Python and solid experience in Python SDK development
  • Experience with Apache Spark or other big data computing engines
  • Excellent leadership and communication skills, with a demonstrated ability to lead technical projects

Preferred experience

  • Experience with autonomous vehicle sensor data (e.g., LiDAR, camera, radar)
  • Experience with ML model training lifecycle (e.g., data preparation, model training / validation / deployment, etc)
  • Understanding of modern AI frameworks (e.g., PyTorch, TensorFlow etc.)
  • Understanding data governance principles, data privacy regulations, and experience implementing security measures to protect data
Qualification wording
Bachelor's degree or higher in Computer Science, Engineering, Robotics, or a similar technical field.
Proficient in Python and solid experience in Python SDK development
Experience with Apache Spark or other big data computing engines
Excellent leadership and communication skills, with a demonstrated ability to lead technical projects
Experience with autonomous vehicle sensor data (e.g., LiDAR, camera, radar)
Experience with ML model training lifecycle (e.g., data preparation, model training / validation / deployment, etc)
Understanding of modern AI frameworks (e.g., PyTorch, TensorFlow etc.)
Understanding data governance principles, data privacy regulations, and experience implementing security measures to protect data
Education & alternatives
Qualifications - 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

Tools in this posting

  • Python
  • Databricks
  • Delta Lake
  • MongoDB
  • PostgreSQL
  • Spark
  • Airflow
  • PyTorch
  • TensorFlow
Source — Tool mentions in context
- 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
- 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)
- 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
- 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)
- 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
- Experience with ML model training lifecycle (e.g., data preparation, model training / validation / deployment, etc) - Understanding of modern AI frameworks (e.g., PyTorch, TensorFlow etc.) - Understanding data governance principles, data privacy regulations, and experience implementing security measures to protect data

About 42dot

42dot is a mobility AI company committed to solving mobility challenges with software and AI.

In the employer’s words · Read in context · Company website ↗

Posting record

Report an error

Open 4 monthsWe first saw this posting 149 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.

Status in our records
Live
First seen by us
Jun 2, 2026 · 149 days ago
Recorded sightings
174
Last seen by us
Oct 29, 2026
Employer says posted
Apr 29, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

Your next step

  • Have your resume and examples of relevant work ready.
  • Check the listed location, eligibility and core experience before starting.

Complete your application on jobs.ashbyhq.com. The employer’s form will show what is required.

Already applied? Track this application

Job description

View original posting ↗

We are looking for the best

About Us

42dot is a mobility AI company committed to solving mobility challenges with software and AI. As the Global Software Center of Hyundai Motor Group, 42dot pioneers the future of mobility by advancing the development of software-defined vehicles.

We develop safety-first, user-centric software-defined vehicle technologies that deliver the latest performance through continuous updates like smartphones. By advancing software and AI technology, 42dot envisions a world where everything is connected and moves autonomously through a self-managing urban transportation operating system.

Our AI Data Pipeline Engineers build up the core data processing pipelines and datasets readiness for autonomous driving cutting edge algorithms. We develop the distributed system of a scalable data pipeline for large-scale dataset (millions of scenes), as well as high-performance data serving SDKs for ML model training / evaluation. The data pipelines we deliver could highly improve the efficiency of ML model development lifecycle, including training, evaluation, deployment, as well as monitoring in the cloud environment.

Responsibilities

  • 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.

Qualifications

  • 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

Preferred Qualifications

  • Experience with autonomous vehicle sensor data (e.g., LiDAR, camera, radar)

  • Experience with ML model training lifecycle (e.g., data preparation, model training / validation / deployment, etc)

  • Understanding of modern AI frameworks (e.g., PyTorch, TensorFlow etc.)

  • Understanding data governance principles, data privacy regulations, and experience implementing security measures to protect data

Interview Process

  • Application Review - Coding Test - 1st interview - 2nd interview - Offer Negotiation - Hiring

  • The screening procedures may vary depending on the position, schedule, or other circumstances.

    You will be individually notified of the screening schedule and results via the email address provided in your application.

Compensation

  • $133,000 - $254,000

Additional Information

  • In accordance with fair hiring practices, do not include any personal information unrelated to your job qualifications (e.g., Social Security Number, family relations, marital status, age, photo, physical condition, place of birth, etc.) in your resume.

  • All documents must be submitted in PDF format and under 30MB in size.

  • If you experience issues uploading your resume, please send it along with the job posting URL to recruit@42dot.ai.

  • We strongly encourage applications from U.S. veterans and candidates eligible for employment preference under applicable laws.

  • Qualified individuals with disabilities are encouraged to apply and will receive consideration under the Americans with Disabilities Act (ADA).

  • 42dot does not accept unsolicited resumes and will not pay fees for any such submissions. Equal Opportunity Statement

  • 42dot is an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees, regardless of race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, or veteran status.

※ Please review the following information before applying.

Source details

View original posting ↗

Source notes

Source excerpts

Selected passages from the saved posting. Check the full description for conditions and exceptions.

Pay
Compensation $133,000 - $254,000 Additional Information
Location & working pattern

San Francisco, Califonia, US

Working pattern and location restrictions need checking in the full posting.

Work authorization

No clear work-authorization passage found. Eligibility is unconfirmed.

See how this role fits your experience

Add your resume to compare the role’s scope, tools and requirements with your experience.

Find answers in the posting

AI
How answers work

AI selects complete passages from this posting. Check them for conditions and exceptions.

Uses this posting and your question. No profile needed.