About the Role

ML Engineer – Focus on Geo-Distributed QAT

• Build a geo-distributed QAT framework to support large-scale training across global infrastructure
• Enable the ML community to deploy their models more easily on SEMRON’s hardware
• Optimize training workflows for heterogeneous and resource-constrained environments

What you should bring in:

• Solid skills in PyTorch
• A solid understanding of current quantization research and hands-on experience with techniques that push performance.

About us

SEMRON develops a 3D scaled AI inference chip, incorporating GPT-3.5-like models on a square cm silicon with minimal power consumption. This revolutionary CMOS-compatible semiconductor technology enables running generative AI at the edge, making it possible for wearable tech, smartphones, and beyond. With a trend towards large foundation models, SEMRON can serve multiple markets with minimal adjustments and simplify the software stack.