Origami Robotics

Robotics · Infrastructure

Full-Stack Robotics Software Engineer

Build the system that turns every robot rollout into traceable training data and every training run into a reproducible, measurable physical evaluation.

Why Origami

Join a small team building the software foundation for general-purpose dexterous manipulation. Your systems will power every robot rollout, training run, and physical evaluation, giving researchers the tools to move faster and making each experiment compound into better robot behavior.

In This Role You Will

You will own critical parts of the learning pipeline and make every experiment reproducible, every model traceable, and every real-world rollout useful.

Data collection → ingestion & validation → dataset creation → model training → task evaluation → failure mining → improved data

  • Own the pipeline from teleoperated robot rollouts to calibrated, synchronized, and versioned multimodal datasets, with tools for replay, visualization, curation, and failure mining.
  • Build reproducible training infrastructure for launching jobs, tracking experiments, managing checkpoints and model lineage, and connecting results back to source data.
  • Build physical evaluation systems with repeatable task runners, held-out tests, result logging, and dashboards.

What We Hope You’ll Bring

  • Strong Python and comfort working in C++.
  • Experience building reliable data, ML, or distributed systems used by other engineers.
  • Experience designing observable, reproducible workflows for multimodal or time-series data.
  • Ability to own and debug systems spanning robot software, sensors, networking, storage, and compute.

Bonus Points If You Have

  • Experience building robot-learning or dexterous-manipulation infrastructure with tools such as ROS2, MCAP, Protobuf, Foxglove, Ray, Slurm, Parquet, or Arrow.
  • Expertise in controls, low-latency software, sensor synchronization, or real-time systems.
  • Built and operated robots through FTC, FRC, Formula SAE, Formula Hybrid, an autonomous vehicle team, or a substantial personal robotics project.

What to include

  1. A robotics data, training, or evaluation system you built and personally owned.
  2. A difficult failure involving real robot data or hardware and how you diagnosed it.
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