ML Research Scientist

SEMRON is developing analog in-memory computing technology for deep neural network acceleration. The ML Research Scientist will develop quantization methods, mathematical modeling techniques, and hardware-aware algorithms to enable efficient, high-accuracy inference on custom silicon, while collaborating with analog hardware engineers on compute primitives.

Responsibilities:

• Research and develop novel analog-aware quantization methods (PTQ and QAT) tailored to in-memory compute constraints
• Design mathematically principled matrix-vector multiplication algorithms that exploit sparsity, noise resilience, and non-idealities to improve hardware efficiency
• Collaborate with analog hardware engineers to define algorithmic requirements and guide co-development of compute primitives