An early-stage AI lab building intelligence grounded in physics rather than language.
Machine Learning Infrastructure Engineer
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.