AI/ML Accelerator Modeling Engineer, Silicon

Be part of a team that pushes boundaries, developing custom silicon solutions that power the future of Google's direct-to-consumer products. You'll contribute to the innovation behind products loved by millions worldwide. Your expertise will shape the next generation of hardware experiences, delivering unparalleled performance, efficiency, and integration.

Google's mission is to organize the world's information and make it universally accessible and useful. Our team combines the best of Google AI, Software, and Hardware to create radically helpful experiences. We research, design, and develop new technologies and hardware to make computing faster, seamless, and more powerful. We aim to make people's lives better through technology.

• Architect and drive the software infrastructure and architecture for on-device AI/ML accelerators.
• Implement, model, analyze, and rigorously test C-models for on-device ML accelerators.
• Develop and maintain robust software environments to support ML accelerator development, testing, and simulation.
• Lead the end-to-end delivery of sophisticated ML accelerator C-models, directly supporting hardware implementation and verification efforts.
• Collaborate cross-functionally with hardware architects, design verification, firmware, and compiler teams to build cycle-approximate models for ML accelerators.

Minimum qualifications:

• Bachelor's degree in Electrical Engineering, Computer Engineering, Computer Science, a related field, or equivalent practical experience.
• 4 years of experience with software development using C, C++ or Python.
• Experience in AI/ML accelerator architecture or reference C-model development.

Preferred qualifications:

• Master's degree or PhD in Electrical Engineering, Computer Engineering or Computer Science, with an emphasis on computer architecture.
  
• Experience in silicon engineering and performance characterization.
• Experience in reference C-model development, performance analysis, and the use of simulation frameworks and profiling tools.
• Experience with CPU or ML accelerator architectures.
• Programming proficiency in C/C++ and Python, specifically applied to system-level modeling and performance optimization.
• Exceptional problem-solving abilities and excellent communication skills, with a proven track record of dissecting complex issues and fostering cross-functional collaboration with engineering teams and leadership.