Overview
Design and build the data platform, frameworks, and developer tooling that power ingestion across Field AI.
Full job description
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.
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.
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 .
Tips for this job
Practical Job and Scholarship guidance. These tips do not replace official rules or create new eligibility requirements.
- Tailor the CV and application to the responsibilities and required skills stated on the official employer page.
- Use concrete evidence of relevant work, projects and measurable results rather than generic claims.
- Confirm location, work authorization, remote restrictions and sponsorship terms before applying.
- Apply through the original employer or official recruitment destination shown on this page.
Verification notes
laptop-ats-crawler v3
Job and Scholarship is the discovery and verification layer. Confirm eligibility, dates, salary/funding and application instructions on the original source before submitting anything.
Field Ai (lever) ↗Browse current Job and Scholarship listings from Field Ai (lever) →
