ML Hardware Architect for SoC & Multimedia Vision

Minimum qualifications: Bachelor's degree in Electrical Engineering, Computer Engineering, Computer Science, a related field, or equivalent practical experience. 3 years of experience with machine learning or multimedia technologies. Experience with architecture or silicon engineering such as computer architecture, DSP circuits, VLSI, or RTL. Experience with Machine Learning frameworks such as TensorFlow and PyTorch. Preferred qualifications: Master's degree or PhD in Computer Science, Electrical Engineering, or a related field. Experience in Machine Learning hardware architecture and computer hardware architecture design. Experience in mobile cameras, computational photography techniques, depth sensing cameras, and others. Understanding of machine learning and image/video/display processing algorithms for mobile photography applications. 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. With your technical expertise, you lead projects in multiple areas of expertise (i.e., engineering domains or systems) within a data center facility, including construction and equipment installation/troubleshooting/debugging with vendors. 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 $127,000-$187,000 + 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. 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 Analyze key Machine Learning workloads and the-related user experience and identify hardware acceleration opportunities. Explore design space and map user experience to hardware and software components on SoC. Design Machine Learning acceleration architecture with comprehensive architectural and quality analyses. Collaborate with algorithm owners to design hardware-friendly networks. Collaborate with cross-functional teams such as research, algorithm, product managers, hardware/software/SoC architecture, and implementation at various design stages. Deliver comprehensive architecture specification and analyses. #J-18808-Ljbffr Google