Unconventional AI is rethinking the foundations of compute to bring biology-scale energy efficiency to AI. Backed by Lightspeed, Sequoia and a16z.
About the role
As a Member of Technical Staff, System Modeling (Performance Models), you will be part of a hands-on R&D team building simulation frameworks that enable evaluation and rapid iteration across all layers of unconventional physics-based computing systems for machine learning workloads. “Extreme co-design” is our guiding principle.
What they're looking for
- Education
- MS/PhD in a quantitative field (AI/ML, Computer Science, Physics, Electrical Engineering, Applied Math), or BS with substantial, clear evidence of equivalent research/engineering depth
- Performance Modeling Knowledge
- Experience with tools and development for power profiling, modeling and simulation for AI workloads
- Deep understanding of spatial architectures and data orchestration mechanisms
- Deep understanding of different dataflow strategies and their tradeoffs, e.g. Weight-Stationary (WS), Output-Stationary (OS), Input-Stationary (IS) and Row-Stationary (RS)
More about this role
Since 2022, AI has entered the mainstream, reshaping entire industries from education and software development to fundamental consumer behaviors. This revolution has created an unprecedented demand for computation - a demand that is now fundamentally limited by energy, not just in the datacenter, but at a global scale.
At Unconventional, our mission is to solve this. We are rethinking computing from the ground up to build a new foundation for AI that is 1000x more efficient. We're doing this by exploiting the rich physics of semiconductors, mapping neural networks directly to the device physics rather than relying on layers of inefficient abstraction.
As a Member of Technical Staff, System Modeling (Performance Models), you will be part of a hands-on R&D team building simulation frameworks that enable evaluation and rapid iteration across all layers of unconventional physics-based computing systems for machine learning workloads. “Extreme co-design” is our guiding principle.
System Modeling is a multi-disciplinary effort, and the team we’re building reflects that. The role involves development of physics-based system models, GPU-accelerated ML system simulations, and cross-layer...
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