Summary
✨ AI‑Generated
An engineering role focused on building robust data platforms for autonomous technology. Responsibilities include creating ingestion frameworks, developing APIs, managing large sensor datasets, and ensuring reliable data operations across distributed environments.
Highlights
Build foundational data platforms for advanced autonomous systems. The role offers opportunities to design scalable infrastructure, developer tools, and integrations supporting complex data workflows.
Description
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
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.
