Machine Learning - Infrastructure

About us

Our mission is to build causal intelligence, starting with physics models to predict and control the weather.

We're building a small team driven by a deep passion and urgency to solve this civilizationally important problem.

Our founding team has led & shipped models across self‑driving cars, humanoid robotics, protein folding, and video generation at world‑class institutions including Google DeepMind, Cruise, Waymo, Meta, Nabla Bio, and Apple.

Responsibilities

• Design, deploy, and maintain large distributed ML training and inference clusters
• Develop efficient, scalable end‑to‑end pipelines to manage petabyte‑scale datasets and model training throughout the entire ML lifecycle
• Research and test various training approaches including parallelization techniques and numerical precision trade‑offs across different model scales
• Analyze, profile and debug low‑level GPU operations to optimize performance
• Stay up‑to‑date on research to bring new ideas to work

What we’re looking for

We value a relentless approach to problem‑solving, rapid execution, and the ability to quickly learn in unfamiliar domains.

You don’t have to meet every single requirement above.

Benefits

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