Responsible for designing and implementing firmware for AI compute platforms, focusing on BMC firmware, code optimization, and system management protocols.

Design and implement scalable system software for high-performance silicon, collaborating across teams to optimize workloads and system performance.

The Hardware System Engineer will design AI compute boards, collaborate across teams, debug hardware issues, and deliver effective silicon products.

The role involves training and optimizing large language models for MatX's hardware, setting up distributed systems for training and inference, and advising on hardware architecture.

The role involves silicon verification, including creating testbenches, driving verification plans, and ensuring silicon accuracy through advanced methodologies.

The ML Performance Engineer develops performance models, writes production libraries for ML, and collaborates on solutions from model to hardware.

The role involves developing scalable silicon physical designs, coordinating with multiple teams, and ensuring performance, power, and area results from RTL to GDSII.

Design and optimize software kernels for specialized hardware, collaborating with ML Research and Hardware Engineering teams to integrate software stacks.

The Architect will deliver silicon architecture for AI models, producing specifications, working closely with teams for effective implementation, and analyzing performance.