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. This isn't a role with a predefined checklist; it's an opportunity to help define the "what" and the "how."
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, hardware/software co-design, or experimental validation in collaboration with other team members. We're hiring exceptional problem-solvers who can navigate deep uncertainty and help chart our technical roadmap.
We are seeking exceptional individuals who can bridge the gap from high-level algorithms to low-level hardware. The ideal candidate has a deep, practical understanding of the modern AI/ML stack and a proven ability to design, train, analyze, and optimize systems for both model quality and computational efficiency.
Algorithmic and System Fluency: Deep understanding of state-of-the-art AI model architectures (e.g., Transformers, Mixture of Experts, Diffusion Models) and their computational properties and their implications on system performance.
Full-Stack Co-Design: A demonstrated ability to identify, debug, and solve quality/performance bottlenecks across the entire stack. This includes experience solving full-stack issues, whether they are in high-level data loaders, algorithmic inefficiencies, and/or hardware-level compute and memory constraints.
Cross-Functional Communication: Excellent ability to communicate complex technical concepts to diverse teams. This includes discussing algorithmic trade-offs with theorists and translating model requirements to hardware and infrastructure engineers.
Modern AI Software Expertise: Proven, hands-on experience in the modern AI/ML software stack. This includes:
While not required, we are particularly interested in candidates who have a forward-looking perspective and have explored areas aligned with our long-term mission: