DFT Engineer
Unconventional AI
DFT Engineer
Unconventional AI
Analog computing substrate for energy-efficient AI
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, DFT Engineer, you will be a foundational member of our multi-disciplinary R&D team. We are looking for individuals who thrive at the intersection of architecture and silicon, turning novel AI concepts into high-performance, energy-efficient hardware. You will be responsible for the testability realization of our novel computing platform, ensuring that our complex digital logic and custom mixed-signal blocks can be reliably tested.
Analog computing substrate for energy-efficient AI
Unconventional AI designs analog AI hardware and silicon substrates that run neural networks directly in hardware. Its chips use analog circuits that mimic biological neuron dynamics to process AI workloads in the physics of silicon, reducing energy use compared with digital GPUs. It differentiates itself by pursuing an in-hardware, neuromorphic-style substrate rather than optimizing existing GPUs, supported by prominent venture funding. Its goal is to counter the AI energy bottleneck and enable scalable AI in data centers with biology-scale efficiency.
Explore more opportunities at Unconventional AI