Machine Learning Modeling Engineer, Silicon

Minimum qualifications:

• Bachelor's degree in Electrical Engineering, Computer Engineering, Computer Science, a related field, or equivalent practical experience.
• 2 years of experience in programming using (C/C++, Python) in industry setting.

Preferred qualifications:

• Master's degree or PhD in Electrical Engineering, Computer Engineering or Computer Science, with an emphasis on computer architecture.
  
• Experience in an SoC development environment.
• Experience in reference model development.
• Experience or knowledge of AI and ML accelerators.

Be part of a diverse 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.

In this role, you will create and maintain a software environment for reference Machine Learning (ML) accelerator c-models. You will develop a system model that expands the team to work across organizations for ML accelerator integration. As a silicon engineer, you will work with architects, implementation designers, verification engineers and SoftWare engineers for providing bit-accurate system c-models and specifications.

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.

The US base salary range for this full-time position is $108,000-$158,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target salaries for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

• Create and maintain software architecture for Machine Learning (ML) accelerator.
• Implement, modeling, analyzing and testing ML accelerator.
• Develop software environment for ML accelerator development and simulation.
• Supporting delivery of ML accelerator c-models for implementation, verification.
• Integrating the ML accelerator into compiler software environment.