Machine Learning Hardware Architect

Minimum qualifications:

• Bachelor's degree in Electrical Engineering, Computer Engineering, Computer Science, a related field, or equivalent practical experience.
   
• 8 years of experience in computer or chip architecture.
• Experience with semiconductor technologies and trends (i.e., including process, memory, interconnect or packaging).
   

Preferred qualifications:

• Master's degree or PhD in Electrical Engineering, Computer Engineering or Computer Science, with an emphasis on computer architecture.
   
• Experience with deep learning frameworks including TensorFlow and PyTorch.
   
• Knowledge of Machine Learning market, technological and business trends, software ecosystem, and emerging applications.
   
• Proven track record architecting hardware solutions for Machine Learning.
   
• Track record of outreach to ML researchers and application developers.
   

About the job

Our computational challenges are so big, complex and unique we can't just purchase off-the-shelf hardware, we've got to make it ourselves. Your team designs and builds the hardware, software and networking technologies that power all of Google's services. As a Hardware Engineer, you design and build the systems that are the heart of the world's largest and most powerful computing infrastructure. You develop from the lowest levels of circuit design to large system design and see those systems all the way through to high volume manufacturing. Your work has the potential to shape the machinery that goes into our cutting-edge data centers affecting millions of Google users.

Our team creates the custom chips at the heart of Google’s Tensor Processing Units. Working with the Google AI community and with external partners, we combine the latest innovations in Machine Learning and integrated circuits to create advanced hardware acceleration solutions for Machine Learning training and inference.
 

Behind everything our users see online is the architecture built by the Technical Infrastructure team to keep it running. From developing and maintaining our data centers to building the next generation of Google platforms, we make Google's product portfolio possible. We're proud to be our engineers' engineers and love voiding warranties by taking things apart so we can rebuild them. We keep our networks up and running, ensuring our users have the best and fastest experience possible.

The US base salary range for this full-time position is $177,000-$266,000 + 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 for new hire 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.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.
 

Responsibilities

• Create differentiated architectural innovations for Google’s semiconductor TPU roadmap.
   
• Monitor industrial and academic trends in artificial intelligence and determine where they should intersect our roadmaps.
• Evaluate the power, performance, and cost of prospective architecture and subsystems.
   
• Engage with system and application software engineers to ensure optimization of the entire hardware/software stack.
   
• Engage with design, verification, and validation engineers to realize the architecture.