# Senior AI Data Pipeline Engineer (Autonomous Driving) at 42dot

> Hybrid · United States · Senior · Software engineering · open. Source: https://alderhq.app/jobs/ashby%3A42dot%3A75e6abe9-9195-43c3-abdf-60feff10bd47 (read 2026-11-13).

## Facts (observed)

- Company: [42dot](https://alderhq.app/companies/42dot)
- Location text: Sunnyvale, United States
- Where it can be done from (inferred): Hybrid · United States (evidence: "Location: Sunnyvale, United States")
- Posted: 2026-04-29 (198 days ago)
- First seen by alder: 2026-11-02 · last verified: 2026-11-13
- Reposted: 0 times · edited: 0 times
- Apply on the employer's site: https://jobs.ashbyhq.com/42dot/75e6abe9-9195-43c3-abdf-60feff10bd47
- Skills listed (inferred): Python, PostgreSQL, MongoDB, Spark, Airflow, PyTorch, TensorFlow, Distributed systems

## Pay and sponsorship

- Posted pay: $133k–$254k per year (from the listing's pay field)
- Market band for similar posted roles (SF Bay Area, n 1213): p25 $182k, median $205k, p75 $226k
- H-1B filings at this company for similar roles, FY26: 2 ([US DOL OFLC LCA disclosure data](https://www.dol.gov/agencies/eta/foreign-labor/performance))

## Description (the employer's text)

### 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.

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Data: alder (https://alderhq.app). Cite https://alderhq.app/jobs/ashby%3A42dot%3A75e6abe9-9195-43c3-abdf-60feff10bd47 and the date you read it. Observed facts come from the employer's own listing; location reach, level, family and skills are inferences.