World Models Researcher for Robotics AI & Self-Supervised Learning

Auxo Talent; San Francisco (CA); On-site; USD 140,000 - 190,000; Full time

Job summary

Auxo Talent partners with an innovative robotics company developing Asimov, an open-source humanoid platform and the full software stack powering it. The Researcher – World Models will work at the intersection of self-supervised representation learning, predictive architectures and embodied control on real robots.

You will design, train and evaluate world models across multimodal data, advance the self-supervised stack, prototype predictive architectures, and own the data pipeline while

Qualifications

• Proven track record of training and evaluating ML models with rigorous evaluation.
• Experience with JEPA or similar predictive architectures.
• Strong data handling and experimentation pipeline skills.
• Experience in robotics or hardware interfacing.
• Publication history or arXiv work is a plus.
• Excellent communication of technical topics.

Responsibilities

• Design and evaluate world models for action prediction across visual, proprioceptive and force/torque modalities.
• Advance self-supervised learning stack for visual and sensor representations.
• Prototype generative and predictive architectures (diffusion, VAEs) against JEPA objectives.
• Own the data pipeline: data curation, tooling and scaling.
• Collaborate with platform/firmware/software teams for deployment to real robots.
• Publish or open-source research to strengthen the field and team goals.

Skills

JEPA

Self-supervised learning

World models

Data pipelines

PyTorch

JAX

Robotics ML

Education

PhD in ML/Robotics/Computer Vision

Tools

PyTorch

JAX

Python

Job description

Auxo Talent partners with an innovative robotics company developing Asimov, an open-source humanoid platform and the full software stack powering it. The Researcher – World Models will work at the intersection of self-supervised representation learning, predictive architectures and embodied control on real robots.

You will design, train and evaluate world models across multimodal data, advance the self-supervised stack, prototype predictive architectures, and own the data pipeline while