This role focuses on researching, designing, and developing security architectures for semiconductor and cryptographic systems, with a specific emphasis on privacy-preserving machine learning using homomorphic encryption for secure AI operations on GPUs. It involves side-channel analysis, strengthening TEE and SEV systems, and designing secure computation frameworks for ML accelerators, contributing to FIPS certification readiness.

This role focuses on developing and designing software for semiconductor operations, specifically involving machine learning algorithms, back-end code generation, and chip compilers within the MLIR framework. The engineer will research, design, develop, and test operating systems-level software, compilers, and network distribution software, applying principles of computer science and engineering.