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 Job

As a Data Platform Engineer, Data Pipelines, you will design and build the systems and integrations that help move data reliably from robots in the field to the teams and services that depend on it — analytics, autonomy, ML training, and deployment operations. You will collaborate with cross-functional teams spanning robotics, autonomy, and deployment to build the data backbone of a field robotics company.

About the Data Platform Team

Every robot we deploy generates a continuous stream of telemetry, sensor logs, and operational data from environments around the world. The Data Platform team builds the systems that capture every autonomy intervention, anomaly, and operational signal from globally deployed robots, classify them, and turn them into the ranked problem list that drives our engineering roadmap.

What You'll Get To Do

Design and build the data platform, frameworks, and developer tooling that power ingestion across Field AI.

Handle the realities of field data: intermittent connectivity, large sensor payloads (LiDAR, camera, IMU), edge-to-cloud synchronization, and backfill from offline deployments.

Develop reusable ingestion SDKs, APIs, and services that enable teams to onboard new robotics data sources with minimal custom code.

Build and maintain integrations across heterogeneous sources: robot/edge systems, fleet management and deployment tooling, simulation outputs, and cloud object storage.

Integrate the platform with downstream consumers: BI tools, ML training and evaluation pipelines, labeling systems, and issue tracking.

Develop connectors and APIs (REST/gRPC, webhooks, CDC) so internal teams can feed data in and consume curated datasets reliably.

Own integration reliability end to end: schema contracts, versioning, retries, backfills, and monitoring.

Optimize pipeline performance, scalability, and cost across growing fleet deployments.

What You Have

Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field.

3–5+ years of experience in data engineering or backend engineering focused on pipelines and infrastructure.

Strong programming skills in Python and SQL (C++, Scala, or Java a plus).

Production experience with streaming systems (Kafka, Kinesis, Pub/Sub) and orchestration tools such as Airflow or Dagster.

Experience with a modern warehouse or lakehouse (BigQuery, Snowflake, Databricks, Redshift) and cloud object storage at scale.

Experience building integrations across systems: third-party APIs, internal services, and CDC/ELT tooling (Fivetran, Airbyte, Debezium, or custom connectors).

Experience building for data quality: testing, monitoring, lineage, and incident response.

Strong problem-solving skills and ability to work in interdisciplinary teams.

The Extras That Set You Apart

Experience with robotics, autonomy, automotive, or other telemetry-heavy operational data (bag files, fleet logs, time-series sensor data).

Familiarity with robotics middleware and log formats such as ROS/ROS2, MCAP, or rosbag.

Experience with edge computing or intermittently connected data collection.

Experience with dbt or similar transformation frameworks.

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.

Field AI

Data Platform Engineer - Data Pipelines

About the Job

Requirements

Responsibilities

Desired Qualifications

About the Job

About the Data Platform Team

What You'll Get To Do

What You Have

The Extras That Set You Apart

About the Company

Field AI

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