Robotics ML Intern: Policy Training & Benchmarks

Baseline Robotics; Zürich; Vor Ort; CHF 30.000 - 36.000; Vollzeit

Zusammenfassung

Baseline Robotics in Zurich, Switzerland, is seeking a motivated ML intern to join our on-site team for a 3–6 month period.

You will train policies, build benchmarks, and run evaluations on real hardware using PyTorch and Python, with access to GPU-accelerated simulators.

Monthly salary is CHF 3,000, and the role offers hands-on experience with diffusion models, RL, and state-of-the-art robotics benchmarks.

Qualifikationen

• Experience training neural networks end-to-end.
• 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.
• Experience with GPU-accelerated simulation tools (Isaac Lab, Newton, mjlab, Genesis).

Aufgaben

• Train policies on demonstration data and run benchmarks on real hardware.
• Build and characterise datasets behind a benchmark, including failure cases and coverage gaps.
• Run policy evaluations across task variations and analyse where success rates break down.
• Reproduce published manipulation results.

Kenntnisse

Neural networks training

Python

PyTorch

Reinforcement learning

Policy learning from demonstrations

Diffusion models

Transformers

Vision-language-action models

GPU-accelerated simulation

Tools

Isaac Lab

Newton

mjlab

Genesis

Jobbeschreibung

Baseline Robotics in Zurich, Switzerland, is seeking a motivated ML intern to join our on-site team for a 3–6 month period.

You will train policies, build benchmarks, and run evaluations on real hardware using PyTorch and Python, with access to GPU-accelerated simulators.

Monthly salary is CHF 3,000, and the role offers hands-on experience with diffusion models, RL, and state-of-the-art robotics benchmarks.