Member of Technical Staff, Models

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 action-conditioned world models on camera and sensor data.
• Use model rollouts for planning and post-training reference policies.
• Find where model predictions differ from the real stations, and why.

What we hope you'll bring

• Experience training world models, video prediction, or latent dynamics models on real data.
• Knowledge of model-based reinforcement learning, planning, and sequence modelling.
• Publications in top machine learning or robotics venues, or equivalent experience.

• Location:
  
  Zurich, Switzerland, on-site 5 days a week.
• Total compensation: CHF 120,.
• Every full-time hire receives stock options as part of the stated total compensation.

Final date to receive applications:
None. Applications will be reviewed on a rolling basis.