Pay
Higher than most similar jobs
$133K–$254K against $127K–$190K, the middle half of what similar US postings state.
From 2,133 postings in the last year. Stated ranges, not salaries paid.
Sunnyvale, United States · San Francisco, Califonia, US
Open 5 months, first seen by us 155 days agoCompensation $133,000 - $254,000 Additional InformationRead the full posting
Location type: HybridFrom the employer’s posting
Employment type: Full-timeFrom the employer’s posting
Department: ENGINEERING › Autonomous DrivingFrom the employer’s posting
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
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
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
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
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
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 ↗
Open 5 monthsWe first saw this posting 155 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Higher than most similar jobs
$133K–$254K against $127K–$190K, the middle half of what similar US postings state.
From 2,133 postings in the last year. Stated ranges, not salaries paid.
Day 155
Up longer than most. Similar jobs usually come down between day 6 and day 54.
From 10,805 similar postings that came down. Coming down is not always a hire.
5 open jobs
Open jobs by the week we first saw them, last 12 weeks.
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- 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
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We file this job under Data Engineer, by the work the posting describes.
Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.
Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.
An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.
The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.
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.
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Compensation $133,000 - $254,000 Additional Information
San Francisco, Califonia, US
Working pattern and location restrictions need checking in the full posting.
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