Machine Learning Engineer, Design Verification, Silicon

This Machine Learning Engineer role at Google focuses on design verification for silicon chips. Responsibilities include researching, designing, and implementing ML/AI algorithms for various verification tasks such as test case generation, coverage analysis, bug prediction, and performance optimization. The engineer will develop and maintain tools for data processing, model training, and evaluation, analyzing large datasets to identify patterns. Building and training ML models for anomaly detection and prediction, evaluating model performance, and participating in verification planning are also key responsibilities. The ideal candidate possesses strong experience with ML/AI frameworks, hardware description languages (Verilog, SystemVerilog, VHDL), and verification methodologies (UVM, OVM). Experience with simulation tools (Synopsys VCS, Cadence Xcelium, Mentor Questa) and proficiency in Python or C++ are essential.