Research Engineer, World Models & Robot Learning (RL)

This is a founding engineer role.You would be one of the first engineers at Tau, working closely with the founders to design and build the core learning systems. This role comes with significant technical ownership and meaningful equity.We are building a general AI for humanoid robots that learns in the real world with minimal human supervision. Our approach is based on world-model-based reinforcement learning trained on large-scale data that is practical to collect. This makes it possible to learn reliable behaviors and improve beyond human performance limits. As a founding engineer, you will design and build core systems while helping shape the technical direction from the ground up.ResponsibilitiesBuild data pipelines that scale to 100k+ hours of multimodal robot dataScale pre- and post-training runs on 1000s of GPUsImprove inference efficiency on low-power embedded systemsLead core architectural decisions, help define the long-term technical roadmap, and set engineering standards from the beginningQualificationsStrong practical experience building software infrastructureExperience implementing and debugging distributed systemsExtensive experience in Python and at least one deep learning library such as PyTorch or JAXIdeally experienced in implementing scalable training pipelines for world-model-based RLExperience with systems programming languages (e.g. Rust, C++) is a plusWe’re a small, focused team, and as an early engineering hire you’ll have outsized impact on both the technical direction and the company’s trajectory, with equity that reflects your role in building Tau from the ground up.