Intern, Robot Learning

About Baseline Robotics

Open source revolutionised how we write software, but its impact on robotics stays limited due to expensive hardware accessible only to well-funded labs. We run that hardware as shared infrastructure for the broader community, billed only for active station time. For a given task, policies are evaluated under similar conditions, giving researchers common ground for fair comparisons.

In this role you will

• Train policies on demonstration data and run benchmarks on real hardware.
• Build benchmark datasets and document their failure cases and coverage gaps.
• Evaluate policies across task variations and reproduce published manipulation results.

What we hope you’ll bring

• Experience training neural networks, with fluency in Python and PyTorch.
• Exposure to diffusion policies, transformers, or vision-language-action (VLA) models.
• Familiarity with reinforcement learning (PPO, SAC) or policy learning on demonstration data.

We encourage you to apply even if you do not believe you meet every qualification.

Details

• Location: Zurich, Switzerland, on-site 5 days a week.
• Duration: 3-6 months.
• Monthly salary: CHF 3,000.

Deadline to apply: None. Applications will be reviewed on a rolling basis.