Robotics Data Infrastructure Engineer

About the Role

This role sits at the intersection of robotics and data infrastructure at a venture-backed robotics startup building the next generation of intelligent robotic systems. You'll be responsible for designing and operating the reliable pipelines and storage systems that make large volumes of robot telemetry and sensor data usable for engineering and ML teams. Your work will directly accelerate iteration speed and enable safer, smarter systems — all within an early-stage, high-ownership environment.

Location: On-site in Los Angeles, CA (candidates in NYC or SF may also be considered). Visa sponsorship is not available for this role.

What You'll Do

• Design and build scalable data pipelines to ingest and process robot telemetry and sensor data (camera, LiDAR, IMU, and more).

• Implement storage solutions and schemas optimized for analytics, model training, and replay use cases.

• Ensure data quality, validation, and lineage across all ingestion and transformation stages.

• Optimize latency and throughput for both real-time streaming and batch processing workloads.

• Instrument observability, monitoring, and alerting across data flows and infrastructure.

• Collaborate closely with robotics engineers and data scientists to translate platform needs into robust implementations.

• Productionize ETL/ELT workflows with CI/CD and automated testing.

• Troubleshoot and resolve production incidents affecting data availability or correctness.

What We're Looking For

Must-haves:

• 3+ years of hands-on experience building and delivering data pipelines specifically for robotics sensor data in a production environment.

• Proven track record designing, building, and maintaining data ingestion, processing, and storage pipelines for sensor modalities such as camera, LiDAR, and IMU.

• Proficiency in Python and/or C++ for building data tooling and pipelines.

• Strong experience with cloud data platforms and distributed processing tools (e.g., AWS or GCP, Kafka or Pub/Sub, Spark or Flink, Airflow).

• Experience with containerization and deployment of data pipelines using Docker and Kubernetes, with basic CI/CD practices.

• Experience with time-series databases and telemetry data management in a robotics context.

• Strong fundamentals in distributed systems, databases, and pipeline design.

• Excellent communication skills and a collaborative mindset for working across engineering and ML teams.

Nice-to-haves:

• Experience with ROS/ROS2 robotics middleware.

• Familiarity with ML workflow tooling such as MLFlow or Kubeflow for end-to-end robotics data pipelines.

• Experience with robotics simulation tools (e.g., Gazebo) and synthetic data generation.

• Prior experience at an early-stage startup.

Compensation & Benefits

Compensation will be discussed during the interview process and is competitive with market rates for this seniority level at an early-stage technology company. Equity participation is part of the overall package.

Location

This is a full-time, on-site role based in Los Angeles, CA. Candidates currently located in New York City, NY or San Francisco, CA will also be considered. Relocation support may be available. Visa sponsorship is not available.