An early-stage AI lab building intelligence grounded in physics rather than language.
Machine Learning Infrastructure Engineer
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Current large language models often mistake correlation for cause, limiting their ability to reason about the physical world. We are constructing the underlying compute fabric to train next-generation systems that learn causality directly from physical laws. You will architect the high-performance clusters and orchestration layers required to push these novel architectures at scale.
What they're looking for
- 3 to 10 years of experience building scalable infrastructure for deep learning workloads.
- Deep proficiency in Python and C/C++ for performance-critical system components.
- Production expertise with Kubernetes and Docker across GCP, AWS, or Azure environments.
- A strong grasp of distributed training challenges and GPU resource optimization.
- Ability to thrive in a small, on-site team solving foundational AI problems.