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, you will be a foundational member of our small, multi-disciplinary R&D team. We are looking for 'first principles' thinkers who are excited to tackle the hardest, most ambiguous technical challenges at the intersection of AI, physics, and computer architecture. You will be responsible for driving invention, prototyping, and validation of the core components of our novel computing platform.
What they're looking for
- A "0-to-1" mindset. You have a demonstrated history of tackling complex, ambiguous R&D problems, often from a blank slate
- Deep curiosity. You are comfortable diving into new domains, whether it's semiconductor physics, machine learning theory, or systems-level design
- A creative and unconventional approach to problem-solving
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, you will be a foundational member of our small, multi-disciplinary R&D team. We are looking for 'first principles' thinkers who are excited to tackle the hardest, most ambiguous technical challenges at the intersection of AI, physics, and computer architecture. You will be responsible for driving invention, prototyping, and validation of the core components of our novel computing platform.
Your work will be fluid and could span from theoretical modeling and simulation to algorithm development,...
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