Robotics ML Intern - Real-World Policy Training & Eval

One Robot; San Francisco (CA); Hybrid; USD 48,000 - 68,000; Full time

Job summary

One Robot in San Francisco is offering an internship to work on real problems with real robots, embedding directly with the technical team and contributing to active research across world models, policy training, and evaluation.

You will code in Python and PyTorch, assist with end-to-end training runs, conduct real-robot evaluations, and help build tooling and data pipelines to improve the evaluation platform. This role emphasizes hands-on work and rapid learning in a small, fast-moving team.

Qualifications

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

Responsibilities

• 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.

Skills

Python

PyTorch

Machine Learning

Education

BS/MS/PhD in ML/robotics/CV

Job description

One Robot in San Francisco is offering an internship to work on real problems with real robots, embedding directly with the technical team and contributing to active research across world models, policy training, and evaluation.

You will code in Python and PyTorch, assist with end-to-end training runs, conduct real-robot evaluations, and help build tooling and data pipelines to improve the evaluation platform. This role emphasizes hands-on work and rapid learning in a small, fast-moving team.