Member of Technical Staff, Reinforcement 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

• Improve policies on the robots with post-training and reinforcement learning.
• Design reward models from vision, language, and operator feedback.
• Stop or recover trials with safety constraints before the hardware is damaged.

What we hope you’ll bring

• Experience training reinforcement-learning systems in robotics, simulation, games, or agents.
• Knowledge of modern policy-gradient and value-based reinforcement learning methods.
• Publications in top machine learning or robotics venues, or equivalent experience.

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.
• Total compensation: CHF 120,000 - 145,000.
• Every full-time hire receives stock options as part of the stated total compensation.

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