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Robotics Data & Software Engineer at early-stage robotics infrastructure startup

Are you ready to solve the biggest bottleneck in robotics? This early-stage startup in San Francisco is looking for a Robotics Data & Software Engineer to own the end-to-end pipeline that turns raw sensor streams into training-ready datasets. You'll architect the infrastructure for multimodal data, synchronize complex streams, and build the foundation that allows models to learn from real-world interactions. If you’re a Python pro with deep AWS experience and a drive to build scalable systems from the ground up, this founding-level role offers the chance to define the data engine of the future.

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Location

San Francisco, United States

Compensation

Not Disclosed + Equity

Company

Confidential company

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Role overview

You will lead the development of high-performance data pipelines, transforming raw sensor streams into training-ready datasets. By architecting scalable infrastructure for multimodal robotics data—including video and force sensing—you’ll enable advanced machine learning models to master complex interactions. This role is central to building the data engine for next-generation intelligent machines.

About the company

Early-stage robotics infrastructure startup

What you will do

  • Build and maintain robust ETL pipelines for synchronizing video, sensor, and robot state data.
  • Architect high-throughput AWS/S3 storage solutions for petabyte-scale multimodal datasets.
  • Develop internal tools for dataset visualization, automated quality assurance, and human-in-the-loop annotation.

Who this is a fit for

  • Strong software engineering fundamentals with deep proficiency in Python and Linux environments.
  • Extensive experience managing large-scale multimodal datasets and cloud infrastructure via AWS.
  • A bias toward automation and execution, capable of turning messy real-world data into structured assets.

Why this role is remarkable

  • Founding-level ownership of the core data infrastructure used to train advanced robotic models.
  • Work at a high-growth, early-stage startup tackling one of the hardest bottlenecks in modern robotics.
  • Direct impact on model performance by defining how large-scale, multimodal data is captured and processed.

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Jill
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