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Open nowPosted 5 days ago

Machine Learning Intern — One Robot (YC W26)

Accel portfolio7,166 open roles

Where
San Francisco, CA, USA
Work mode
On site
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Your applicationOpen nowMachine Learning Intern — One Robot (YC W26)Accel portfolio · San Francisco, CA, USA

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The clock on this job

Early applications get read.

9.5% of postings close within 7 days. Measured by our own scanner across the market. Accel portfolio postings stay open a median of 28 days.

Share of postings closed within
  1. 1.8%1 day
  2. 3.9%3 days
  3. 9.5%7 days
  4. 15.5%14 days
  5. 33.9%30 days
This job: posted 5 days ago

Accel portfolio median: 28 days open

The posting

One Robot builds task-specific world models and an evaluation platform for robot manipulation policies.

Training end-to-end policies for robots is vibes-based today. Teams collect data, train, deploy on a real robot, find out what fails, collect more, retry. We replace the trial-and-error with rigorous validation that tells you where your policy will fail and what data to collect to fix it.

Robotics can't industrialize without an evaluation layer. We're building it.

We're based in San Francisco, backed by Accel, YC, several exited founders, and engineering leaders at leading AI companies. We're small and deliberately so — everyone owns a wide surface area and moves fast.

This internship is for people who want to work on real problems with real robots, not toy datasets. You'll embed directly with the technical team and contribute to active research across world models, policy training, and evaluation.

What you'll do:

  • Contribute to training runs: Work alongside founding engineers on world model or eval model experiments end-to-end
  • Run real-robot evaluations: Collect demonstration data, run policies on physical hardware, and document failure modes
  • Build tooling: Write Python and PyTorch code that improves our data engine, training pipelines, or eval infrastructure
  • Close the sim-to-real gap: Run experiments that test how well simulation predicts real-robot behavior

Requirements:

  • Strong coding in Python and PyTorch
  • Currently enrolled in a BS, MS, or PhD program in ML, robotics, computer vision, or a related field
  • Hands-on experience training or fine-tuning a generative model, VLM, or policy (coursework or research counts)
  • Ability to work in-person in San Francisco

Nice to have:

  • Experience with real robot hardware or simulation environments (Isaac, MuJoCo, etc.)
  • Prior research in manipulation, 3D vision, or model evaluation
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