Machine Learning IP Architect

Key Skills

3D Modeling & Rigging, Design, Machine learning techniques, Server architectures, Software Testing

Job Description

Minimum qualifications:

• Bachelor's degree in Computer Science, Electrical Engineering, a related field, or equivalent practical experience.
• 15 years of experience in roles supporting architecture, micro-architecture, modeling, design, and verification initiatives.
• Experience in compute or memory subsystems.

Preferred qualifications:

• 20 years of experience in silicon with complex processor-class SoCs.
• Process and methodology experience around IP development and integration into SOCs.
• Deep understanding of all facets of high performance computing including programmable processing, hierarchical memory subsystems, and advanced interconnects.
• Ability to perform architectural and performance analysis combining product requirements, design parameters, modeling, and compiler/Software/Hardware interdependencies.
• Track record of successful product delivery and deployment.

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.

As Machine Learning Hardware Architect within Google's Hardware team, you will help deliver products that have an impact on the Technical Infrastructure that powers Google. You will play a major role in our Tensor Processing Unit (TPU) roadmap by providing technical leadership for our strategic IP. In this role, you will turn product and SOC feature/performance requirements into high-performance optimized ML IP architectures and microarchitectures. Follow-through to IP development and successful product deployment is a key measure of success.

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 $216,000-$317,000 + 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

• Perform IP architecture/microarchitecture and subsequent IP development in collaboration with architecture, performance, systems, compiler, and other functional teams.
• Participate in defining leadership Machine Learning IP roadmap.
• Partner with other silicon functions in an IP/SOC development model.