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Robotics Data Infrastructure Engineer

Remote, United States remote Mid Salary not listed
remote Mid level Technology & IT Curated
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About the role

About the Role
This role sits at the intersection of robotics and data infrastructure at a well-funded, early-stage robotics company. You'll be responsible for building 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 enable faster iteration and safer robotic systems — from raw sensor ingestion all the way through to training-ready datasets and real-time analytics.
You'll join a cross-functional team of robotics engineers, software engineers, and data scientists in a fast-paced, on-site environment in Los Angeles, CA. This is a high-impact, hands-on role with broad scope at a company building at the frontier of physical AI and robotics.
Please note: 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 that support analytics, model training, and data replay.

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

Optimize latency and throughput for both real-time and batch processing use cases.

Instrument observability, monitoring, and alerting for data flows and infrastructure.

Collaborate closely with robotics engineers and data scientists to translate platform needs into production-grade 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
Required:

3+ years of hands-on experience building data infrastructure or engineering pipelines specifically for robotics sensor data — this is a dealbreaker requirement.

Proven experience designing, building, and maintaining data ingestion, processing, and storage pipelines for sensor data (e.g., camera, LiDAR, IMU).

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

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

Hands-on 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, plus basic CI/CD.

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

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

Nice to Have:

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 in an early-stage or high-growth startup environment.

Location
This is a full-time, on-site role based in Los Angeles, CA. Candidates based in or willing to relocate to the Los Angeles area are strongly preferred. The company also has a presence in New York City, NY and San Francisco, CA.
Compensation & Benefits
Compensation will be competitive and commensurate with experience, including equity participation appropriate for an early-stage company. Specific details will be shared during the interview process.
Originally posted on Himalayas

Interview prep

Walk in with sharper answers.

Use this as a quick practice sheet before you speak with the employer.

Mid
Technology & IT Data Analysis Python Sales Robotics Data Mid level

Likely questions

  1. Tell us about work you have done that is close to the Robotics Data Infrastructure Engineer role.
  2. How would you approach your first 30 days at name?
  3. Which of Data Analysis, Python and Sales have you used recently, and what did it help you achieve?
  4. Describe a time you solved a problem without waiting to be told exactly what to do.
  5. How do you stay organised and communicate clearly when working remotely?

Prepare before the call

  • A recent example that proves your experience with Data Analysis, Python and Sales.
  • One short story with a problem, your action, and the result.
  • Two examples that show the strengths listed on your CV.
  • A clear reason why this role and company interest you.
  • Your availability, preferred work style, and salary expectations.

Ask them

  • What would success look like in the first 90 days?
  • What are the main problems this hire should help solve?
  • How does the team give feedback and measure good work?
  • What does a normal working week look like for this role?
Practice line

I am interested in the Robotics Data Infrastructure Engineer role because I can bring practical experience in Data Analysis, Python and Sales, learn the team quickly, and contribute to the outcomes name needs from this hire.

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