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Google Tpu Jobs (NOW HIRING)

You will have an opportunity to drive cutting-edge TPU (Tensor Processing Unit) technology that powers Google's most demanding AI/ML applications. You'll be part of a team that pushes boundaries ...

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Google Tpu information

What are the key skills and qualifications needed to thrive in the Google Tpu position, and why are they important?

To excel in a Google TPU role (such as TPU Software Engineer or TPU Systems Architect), you need strong expertise in computer science, machine learning, and hardware acceleration, often supported by a degree in a related field. Experience with TensorFlow, distributed computing environments, and custom accelerator programming is highly valued, along with familiarity with performance profiling tools. Problem-solving abilities, clear communication, and collaboration skills are important for designing solutions and working across multidimensional teams. These skills are critical to effectively develop and optimize TPU-based systems that advance machine learning research and applications.

What are some typical projects or responsibilities for professionals working with Google TPU technology?

Professionals working with Google TPU technology often engage in designing and implementing machine learning models optimized for TPU hardware, supporting large-scale research, and enhancing AI infrastructure performance. Daily tasks may include collaborating with data scientists and software engineers, fine-tuning models for accelerated inference, debugging performance bottlenecks, and contributing to the development of new TPU features or software stacks. Team structures are highly collaborative, often involving cross-functional partnerships to deliver scalable, innovative AI solutions. These roles offer opportunities to work on cutting-edge AI challenges and contribute to advancements in both software and hardware optimization.

What is a Google TPU job?

A Google TPU job typically involves working with Tensor Processing Units (TPUs), which are specialized hardware accelerators designed for machine learning tasks. Professionals in this role develop, optimize, and deploy deep learning models using TPUs to improve training speed and efficiency. They may work on software frameworks like TensorFlow, create scalable AI solutions, and collaborate with researchers and engineers to enhance TPU performance.

More about Google Tpu jobs
What cities are hiring for Google Tpu jobs? Cities with the most Google Tpu job openings:
What are the most commonly searched types of Google Tpu jobs? The most popular types of Google Tpu jobs are:
What states have the most Google Tpu jobs? States with the most job openings for Google Tpu jobs include:
Infographic showing various Google Tpu job openings in the United States as of May 2026, with employment types broken down into 88% Full Time, 7% Part Time, and 5% Contract. Highlights an 92% Physical, 1% Hybrid, and 7% Remote job distribution.

SoC Silicon Top-Level Floorplan Engineer

Google

Sunnyvale, CA • On-site

Full-time

Posted 17 days ago


Google rating

8.8

Company rating: 8.8 out of 10

Based on 92 frontline employees who took The Breakroom Quiz

31st of 186 rated software companies


Job description

Minimum qualifications:
  • Bachelor's degree in Electrical Engineering, Computer Engineering, Computer Science, or a related field, or equivalent practical experience.
  • 10 years of experience in physical design (e.g., with a focus on floorplanning, integration, or top-level chip assembly).
  • Experience in 3D Integrated Circuit (3D IC) design (e.g., multi-die partitioning, TSV planning, advanced chiplet and packaging technologies, optimizing PPA, and physical verification in a SiP context).
  • Experience in physical design working on advanced nodes.
  • Experience collaborating with cross-functional teams (e.g., architecture, RTL design, synthesis, verification).

Preferred qualifications:
  • Master's degree or PhD in Electrical Engineering, Computer Engineering, or Computer Science with an emphasis on computer architecture.
  • Experience in scripting languages (e.g., Python, Tcl, or Perl) and industry standard tools including Innovus, FusionCompiler.
  • Experience working on various technologies (e.g., embedded processors, DDR, SerDes, HBM, networking-on-chip fabrics, etc.).
  • Experience using EDA tools to resolve DRC/LVS/EMIR issues for leading edge nodes.
  • Experience with SoC design methodologies for full-chip power grid, global clocking, data path implementation, 3PIP integration, and bump planning.

About the job
In this role, you'll work to shape the future of AI/ML hardware acceleration. You will have an opportunity to drive cutting-edge TPU (Tensor Processing Unit) technology that powers Google's most demanding AI/ML applications. You'll be part of a team that pushes boundaries, developing custom silicon solutions that power the future of Google's TPU. You'll contribute to the innovation behind products loved by millions worldwide, and leverage your design and verification expertise to verify complex digital designs, with a specific focus on TPU architecture and its integration within AI/ML-driven systems.
In this role, you will be creating the initial physical layout of a chip top-level, defining block sizing/placement, power grids, and clock distribution to meet performance, power, and area (PPA) goals; requiring collaboration with architecture, RTL, and synthesis teams, using industry and internal tools, and driving early timing/congestion closure for modern SoCs. You will utilize full-chip planning and IP integration, delivering floor plan collaterals and collaborating for sign-off. This is a cross-functional and central role that will require interactions with numerous development teams.
The AI and Infrastructure team is redefining what's possible. We empower Google customers with breakthrough capabilities and insights by delivering AI and Infrastructure at unparalleled scale, efficiency, reliability and velocity. Our customers include Googlers, Google Cloud customers, and billions of Google users worldwide.
We're the driving force behind Google's groundbreaking innovations, empowering the development of our cutting-edge AI models, delivering unparalleled computing power to global services, and providing the essential platforms that enable developers to build the future. From software to hardware our teams are shaping the future of world-leading hyperscale computing, with key teams working on the development of our TPUs, Vertex AI for Google Cloud, Google Global Networking, Data Center operations, systems research, and much more.
The US base salary range for this full-time position is $192,000-$278,000 bonus equity benefits. Our salary ranges are determined by role, level, and location. 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
  • Own the planning, creation, and delivery of top-level floorplan deliverables and implementation for Silicon SOC projects from concept to working silicon volume.
  • Resolve structural or physical issues related to the integration of ASICs and SoCs, and collaborate with teams across Google to develop ideas for silicon and hardware projects.
  • Manage all cross-functional interactions related to top-level floorplanning of chip projects.
  • Develop and improve floorplan implementation methodologies. Support and execute implementation flows using both industry-standard and specialized internal tools.
  • Perform technical evaluations of vendors and IP, providing recommendations and assessments of process node trade-offs to meet PPA, and cost goals.

Information collected and processed as part of your Google Careers profile, and any job applications you choose to submit is subject to Google's Applicant and Candidate Privacy Policy .
Google is proud to be an equal opportunity and affirmative action employer. We are committed to building a workforce that is representative of the users we serve, creating a culture of belonging, and providing an equal employment opportunity regardless of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), expecting or parents-to-be, criminal histories consistent with legal requirements, or any other basis protected by law. See also Google's EEO Policy , Know your rights: workplace discrimination is illegal , Belonging at Google , and How we hire .
If you have a need that requires accommodation, please let us know by completing our Accommodations for Applicants form .
Google is a global company and, in order to facilitate efficient collaboration and communication globally, English proficiency is a requirement for all roles unless stated otherwise in the job posting.
To all recruitment agencies: Google does not accept agency resumes. Please do not forward resumes to our jobs alias, Google employees, or any other organization location. Google is not responsible for any fees related to unsolicited resumes.

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