Machine Learning Researcher

Early-stage AI lab building intelligence that learns causality through physics. You are a researcher who believes true intelligence emerges from understanding physical laws rather than statistical patterns in language. Your days will be spent architecting novel PyTorch models that infer causal structures from raw data, moving beyond correlation to grasp the mechanics of how the world works. We offer the autonomy to pursue deep, fundamental questions in a focused, on-site environment in San Francisco where every line of code advances the frontier of causal reasoning. What we're looking for: 1+ years of hands-on experience building and training models in PyTorch Strong foundation in Python and scientific computing libraries Deep interest in causal inference, physics-based modeling, or representation learning Proven ability to translate complex research concepts into robust engineering implementations Preference for deep focus and collaborative problem-solving over corporate process Must be based in the United States. Tech stack: Python, PyTorch #J-18808-Ljbffr