Member of Technical Staff, Reinforcement Learning

Baseline Robotics; Zürich; On-site; CHF 120,000 - 145,000; Full time

Benefits offered by this job

Stock options

Job summary

Baseline Robotics in Zurich, Switzerland, on-site 5 days a week, is seeking an AI scientist to advance reinforcement learning for robotic control and policy improvement on our shared hardware platform.

You will work on post-training policy improvements, safety-focused exploration, and developing reward models from vision, language, and operator feedback. A strong RL background in robotics, simulations, or games and publications or equivalent experience are highly valued.

Qualifications

• 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.

Responsibilities

• 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.

Skills

RL in robotics

Policy gradients

Publications in ML/Robotics

Job description

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.

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.