Senior Data Platform Engineer
Irvine, CA
- Pay
USD 160,000–200,000/year — pay source
Salary 160,000 – 200,000 USD per year Our salary range is generous and we consider each individual’s background and experience when determining final compensation. Base pay may vary based on role scope, job-related knowledge, skills, experience, and the Irvine, California market.
Read the full posting- Work setting
On-site — work setting source
Work setup in the employer’s listing: onsite
From the employer’s posting- Employment
Full-time — employment source
Employment type Full time
Employment type in the employer’s listing: Full time
From the employer’s posting
What you’ll work on
Full postingWe are building the data foundation that powers the full machine learning lifecycle for autonomous robotics.
Design scalable architecture for large multimodal robotics and ML datasets
Build pipelines that turn raw robot data into versioned, ML-ready data products
Build automated validation and data-quality checks that catch bad data early
Track provenance and lineage across raw data, labels, datasets and ML workloads
Design for incremental processing, reprocessing, backfills and versioned transforms
From the employer’s posting
We are building the data foundation that powers the full machine learning lifecycle for autonomous robotics. Our robots generate large-scale, multimodal datasets across real-world deployments, and turning that raw experience into reliable, discoverable, high-quality ML data is a core part of improving our autonomy systems.As a Data Platform Engineer, you will help design and build the platform that manages data from ingestion through processing, validation, labeling, dataset generation, training, and evaluation.This is not a traditional analytics data engineering role. You will work closely with ML engineers, researchers, labeling teams, robotics engineers, and infrastructure engineers to build scalable systems for robotics and ML data.
Design and build scalable data architecture for large-scale multimodal robotics and ML datasets.
Develop reliable pipelines for transforming raw robot data into versioned, ML-ready data products.
Develop automated validation and data-quality frameworks that detect incomplete, corrupted, or unusable data early.
Build systems for tracking provenance and lineage across raw data, derived artifacts, labels, datasets, and downstream ML workloads.
Design for incremental processing, reprocessing, backfills, and versioned transformations.
Tools in this posting
- C++
- Java
- Python
- Kubernetes
- S3
- Spark
- Airflow
- Dagster
- Go
Source — Tool mentions in context
- Strong experience building production data platforms or large-scale data-processing systems. - Strong software engineering skills, preferably Python and/or C++/Java/Go. - Experience with distributed data processing and workflow orchestration.
- Strong understanding of data quality, lineage, reproducibility, and reliable pipeline design. - Experience with technologies such as S3, Airflow/Dagster, Spark/Ray, Kubernetes, Parquet, or similar systems. - Ability to work across ambiguous organizational and technical boundaries.
Posting record
Report an error- Status in our records
- Live
- First seen by us
- Oct 6, 2026 · 18 days ago
- Recorded sightings
- 23
- Last seen by us
- Oct 24, 2026
- Employer says posted
- Sep 13, 2026
These dates show when we found the listing. Check the employer’s website to confirm it is still accepting applications.
Your next step
- Have your resume and examples of relevant work ready.
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Job description
About the Role
We are building the data foundation that powers the full machine learning lifecycle for autonomous robotics. Our robots generate large-scale, multimodal datasets across real-world deployments, and turning that raw experience into reliable, discoverable, high-quality ML data is a core part of improving our autonomy systems.As a Data Platform Engineer, you will help design and build the platform that manages data from ingestion through processing, validation, labeling, dataset generation, training, and evaluation.This is not a traditional analytics data engineering role. You will work closely with ML engineers, researchers, labeling teams, robotics engineers, and infrastructure engineers to build scalable systems for robotics and ML data.
What You'll Do
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Design and build scalable data architecture for large-scale multimodal robotics and ML datasets.
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Build abstractions and services for ingestion, processing, datasets, metadata, lineage, and data quality.
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Develop reliable pipelines for transforming raw robot data into versioned, ML-ready data products.
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Define data models, schemas, contracts, and lifecycle states across data-processing workflows.
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Build systems for tracking provenance and lineage across raw data, derived artifacts, labels, datasets, and downstream ML workloads.
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Develop automated validation and data-quality frameworks that detect incomplete, corrupted, or unusable data early.
-
Design for incremental processing, reprocessing, backfills, and versioned transformations.
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Improve observability and failure diagnosis across complex data workflows.
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Partner with ML and robotics teams to understand domain-specific data requirements and turn recurring patterns into reusable platform capabilities.
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Work closely with infrastructure/platform teams on storage, compute, orchestration, reliability, and scalability.
What We're Looking For
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Strong experience building production data platforms or large-scale data-processing systems.
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Strong software engineering skills, preferably Python and/or C++/Java/Go.
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Experience with distributed data processing and workflow orchestration.
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Experience with data lakes/lakehouses, object storage, metadata systems, schemas, and data versioning.
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Strong understanding of data quality, lineage, reproducibility, and reliable pipeline design.
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Experience with technologies such as S3, Airflow/Dagster, Spark/Ray, Kubernetes, Parquet, or similar systems.
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Ability to work across ambiguous organizational and technical boundaries.
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Strong systems-design and engineering judgment.
Nice to Have
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Experience with ML datasets or ML infrastructure.
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Robotics, autonomous vehicles, sensor, video, image, LiDAR, or other multimodal data.
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Experience building internal developer/platform products.
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Experience operating pipelines at TB/PB scale.
Salary
160,000 – 200,000 USD per year
Employment type
Full time
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
Salary 160,000 – 200,000 USD per year Our salary range is generous and we consider each individual’s background and experience when determining final compensation. Base pay may vary based on role scope, job-related knowledge, skills, experience, and the Irvine, California market.
- Location & working pattern
Irvine, CA
Working pattern and location restrictions need checking in the full posting.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.
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