Job description

FieldAI ’s Irvine team is where embodied AI meets real robots, real sensors, and real field deployments. Based in the heart of Southern California’s robotics ecosystem, we build risk-aware, reliable, field-ready AI systems that solve the hardest problems in robotics and unlock the full potential of embodied intelligence. If you want your work to ship, get tested on hardware, and improve through real deployments, Irvine is the place. We go beyond typical data-driven approaches or pure transformer-only architectures, combining rigorous engineering with learning systems proven in globally deployed solutions that deliver results today and get better every time our robots run in the field. 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 Design and build scalable data architecture for large-scale multimodal robotics and ML datasets. Build abstractions and services for ingestion, processing, datasets, metadata, lineage, and data quality. Develop reliable pipelines for transforming raw robot data into versioned, ML-ready data products. Define data models, schemas, contracts, and lifecycle states across data-processing workflows. Build systems for tracking provenance and lineage across raw data, derived artifacts, labels, datasets, and downstream ML workloads. Develop automated validation and data-quality frameworks that detect incomplete, corrupted, or unusable data early. Design for incremental processing, reprocessing, backfills, and versioned transformations. Improve observability and failure diagnosis across complex data workflows. Partner with ML and robotics teams to understand domain-specific data requirements and turn recurring patterns into reusable platform capabilities. Work closely with infrastructure/platform teams on storage, compute, orchestration, reliability, and scalability. What We're Looking For 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. Experience with data lakes/lakehouses, object storage, metadata systems, schemas, and data versioning. 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. Strong systems-design and engineering judgment. Nice to Have Experience with ML datasets or ML infrastructure. Robotics, autonomous vehicles, sensor, video, image, LiDAR, or other multimodal data. Experience building internal developer/platform products. Experience operating pipelines at TB/PB scale. 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. Why Join FieldAI in Irvine? In Irvine, you will work where the robots are. Our local team builds and tests systems on real hardware with real sensors, then ships them to operate in unstructured, previously unknown environments around the world. We are solving one of robotics’ hardest challenges: reliable deployment outside the lab. Our Field Foundational Models™ raise the bar for perception, planning, localization, and manipulation, with an emphasis on explainability and safety for real-world use. You will collaborate with a world-class team that thrives on creativity, resilience, and bold thinking. We bring deep experience from organizations such as DeepMind, NASA JPL, Boston Dynamics, NVIDIA, Amazon, Tesla Autopilot, Cruise, Zoox, Toyota Research Institute, and SpaceX, along with a track record of field deployments and strong performance in DARPA challenge segments. Be Part of the Next Robotics Revolution We are looking for builders who want their work to leave the whiteboard and show up on robots. If you enjoy tackling tough, uncharted questions and working across disciplines, you will find your people here. Our teams span AI, software, robotics engineering, product, field deployment, and technical communication, all focused on shipping systems that perform in the real world. Our headquarters is in Irvine, and we partner closely with teams there as well as colleagues across the US and around the world. Join us in Southern California and help define what dependable, field-ready autonomy looks like. We value diverse perspectives and are committed to fostering an inclusive workplace. We evaluate candidates and employees based on merit, qualifications, and performance, and we do not discriminate on the basis of race, color, gender, national origin, ethnicity, veteran status, disability status, age, sexual orientation, gender identity, marital status, or any other legally protected status.

Requirements

Must-haves

Design and build scalable data architecture for large-scale multimodal robotics and ML datasets.
Build abstractions and services for ingestion, processing, datasets, metadata, lineage, and data quality.
Develop reliable pipelines for transforming raw robot data into versioned, ML-ready data products.
Define data models, schemas, contracts, and lifecycle states across data-processing workflows.
Build systems for tracking provenance and lineage across raw data, derived artifacts, labels, datasets, and downstream ML workloads.
Develop automated validation and data-quality frameworks that detect incomplete, corrupted, or unusable data early.
Design for incremental processing, reprocessing, backfills, and versioned transformations.
Improve observability and failure diagnosis across complex data workflows.
Partner with ML and robotics teams to understand domain-specific data requirements and turn recurring patterns into reusable platform capabilities.
Work closely with infrastructure/platform teams on storage, compute, orchestration, reliability, and scalability.
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.
Experience with data lakes/lakehouses, object storage, metadata systems, schemas, and data versioning.
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.
Strong systems-design and engineering judgment.

Nice-to-haves

Experience with ML datasets or ML infrastructure.
Robotics, autonomous vehicles, sensor, video, image, LiDAR, or other multimodal data.
Experience building internal developer/platform products.
Experience operating pipelines at TB/PB scale.
Why Join FieldAI in Irvine?
Be Part of the Next Robotics Revolution

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aigomachine learningmlpythonjavakubernetes

Platform: lever
Effort: quick