Data Platform Engineer, Infrastructure

Field AI · Los Angeles

Software EngineeringEngineeringOn-siteFull timeposted 8w ago

Location: Irvine, CA

Field AI is transforming how robots interact with the real world. We are building risk-aware, reliable, and field-ready AI systems that address the most complex challenges in robotics, unlocking the full potential of embodied intelligence. We go beyond typical data-driven(1) approaches or pure transformer-based architectures, and are charting a new course, with already-globally-deployed solutions delivering real-world results and rapidly improving models through real-field applications.

About Field AI

Field AI is at the forefront of robotic embodied AI, transforming industries like construction, security, mining, and manufacturing. Our autonomous robots operate globally, often in harsh environments, delivering critical insights to customers. Whether monitoring construction progress, ensuring safety compliance, or conducting predictive maintenance, Field AI is advancing technology to make a meaningful impact.

Learn more at https://fieldai.com.

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.

About the Job

As a Data Platform Engineer, Infrastructure, you will build and operate the cloud foundation the entire data platform runs on — the systems every robot log, dashboard, and model-training run depends on. You will collaborate with pipeline and analytics engineers, as well as edge and robotics teams, to keep the platform reliable, secure, and cost-efficient as our fleet grows.

What You'll Get To Do

Design, build, and operate the cloud infrastructure for the data platform: compute (Kubernetes, serverless, batch clusters), storage (object stores, warehouse/lakehouse), and networking.

Manage everything as code: Terraform/IaC, GitOps workflows, and CI/CD for infrastructure and data services.

Provision and tune infrastructure for heavy workloads: large-scale sensor data processing, distributed pipeline execution, and ML training and evaluation jobs.

Own platform reliability: SLAs/SLOs, on-call practices, incident response, and capacity planning as fleet data volume grows.

Implement security and governance: IAM and access controls, secrets management, encryption, audit logging, and environment isolation.

Own cloud cost management: monitoring, budgeting, and optimization across storage and compute.

Build the observability stack (metrics, logging, tracing) for all data platform services.

Build internal tooling and paved paths so pipeline and analytics engineers can ship without becoming infrastructure experts.

What You Have

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

3–5+ years of experience in infrastructure, platform, DevOps, or SRE roles, ideally supporting data-intensive systems.

Strong experience with a major cloud (AWS or GCP), Kubernetes, and infrastructure-as-code (Terraform or similar).

Strong programming skills in Python, Go, or similar for automation and internal tooling.

Experience operating production systems: monitoring, alerting, incident response, and capacity planning.

Working knowledge of data infrastructure components (warehouses, object storage, streaming systems, orchestrators) and what they demand from underlying infrastructure.

Experience with security fundamentals: IAM, network security, secrets management.

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

The Extras That Set You Apart

Experience supporting data or ML platforms specifically (Spark/Databricks clusters, GPU scheduling, feature stores).

Experience with high-volume telemetry or IoT/edge fleets.

Track record of significant cloud cost optimization.

Prior experience as an early platform/infrastructure hire, building from zero.

Field AI Onsite Work Philosophy:

Field AI believes in-person collaboration is essential for tackling complex challenges. These are fully onsite roles based in our Irvine office, with flexible hours to support work-life balance.

We are committed to fostering a diverse and inclusive workplace and encourage candidates from all backgrounds to apply.

Why Join Field AI?

We are solving one of the world's most complex challenges: deploying robots in unstructured, previously unknown environments. Our Field Foundational Models™ set a new standard in perception, planning, localization, and manipulation, ensuring our approach is explainable and safe for deployment. The data platform this team builds will carry every signal our robots produce — the raw material behind every autonomy improvement we ship.

You will have the opportunity to work with a world-class team that thrives on creativity, resilience, and bold thinking. With a decade-long track record of deploying solutions in the field, winning DARPA challenge segments, and bringing expertise from organizations like DeepMind, NASA JPL, Boston Dynamics, NVIDIA, Amazon, Tesla Autopilot, Cruise Self-Driving, Zoox, Toyota Research Institute, and SpaceX, we are set to achieve our ambitious goals.

Be Part of the Next Robotics Revolution

To tackle such ambitious challenges, we need a team as unique as our vision — innovators who go beyond conventional methods and are eager to tackle tough, uncharted questions. We're seeking individuals who challenge the status quo, dive into uncharted territory, and bring interdisciplinary expertise. Our team requires not only top AI talent but also exceptional software developers, engineers, product designers, field deployment experts, and communicators.

Join us, shape the future, and be part of a fun, close-knit team on an exciting journey!

We celebrate diversity and are committed to creating an inclusive environment for all employees. Candidates and employees are always evaluated based on merit, qualifications, and performance. We will never discriminate on the basis of race, color, gender, national origin, ethnicity, veteran status, disability status, age, sexual orientation, gender identity, marital status, mental or physical disability, or any other legally protected status.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.