Robotics ML Research Scientist – Foundation Models

Enact; Zürich; Presencial; CHF 120.000 - 170.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Impactful work

Fast-paced learning

Ownership from day one

Visa sponsorship & relocation

Zurich in-person setup

Equity participation

Descripción de la vacante

Enact in Zürich is hiring to build the base intelligence layer for robotics, training large-scale force-aware foundation models to enable dexterous manipulation across tasks and environments.

You will design architectures and training curricula, own end-to-end experiments from data specification to real-robot evaluation, and build data mixes to train and assess robots in real-world and simulated settings. Strong ML fundamentals and PhD or equivalent research are expected.

Formación

• Experience building large-scale predictive or generative models (RSSM/JEPA/transformer/diffusion).
• Strong stats and ML fundamentals; design rigorous experiments.
• PhD or equivalent research with ML/vision/robotics publications.

Responsabilidades

• Design and run large-scale pre-training for robot foundation models; define architectures and curricula.
• Own experiments end-to-end from data spec to real-robot evaluation; study scaling laws and data quality.
• Create data mixes and evaluation sets for novel, high-precision tasks across real and simulated settings.
• Research methods to improve sample efficiency and robustness across deployment environments.

Conocimientos

Large-scale models

Probabilistic reasoning

Experiment design

Robotics/ML knowledge

Educación

PhD or equivalent

Herramientas

PyTorch

JAX

Descripción del empleo

Enact in Zürich is hiring to build the base intelligence layer for robotics, training large-scale force-aware foundation models to enable dexterous manipulation across tasks and environments.

You will design architectures and training curricula, own end-to-end experiments from data specification to real-robot evaluation, and build data mixes to train and assess robots in real-world and simulated settings. Strong ML fundamentals and PhD or equivalent research are expected.