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Physical Design Engineer, 3D Technology, PhD, University Graduate

Google

Physical Design Engineer, 3D Technology, PhD, University Graduate

Google

·

On-site

·

Full-time

·

1mo ago

Compensation

$132,000 - $189,000

Benefits & Perks

Health benefits

Creative environment

Remote options

Competitive salary and equity

Healthcare

Required Skills

Figma

Sketch

InVision

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 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.

As a Physical Design Engineer in 3D Technology, you will collaborate with technology, physical design, circuit design, and hardware architecture teams to overcome the slowing of Moore’s Law while delivering ASIC’s and SoC’s. You will help develop new 3D technology physical design methodologies to drive best product Power Performance Area (PPA) by optimizing across technology, digital block implementation, clock distribution, floorplanning, circuits, memories, and third-party IPs. You will drive new physical design flows that co-optimize across the entire design methodology space, including 3D and see these through from inception to maturity and tapeout. This will include high impact physical design innovations with through-silicon vias (TSVs) requiring methodology and verification flow development and ratification. As part of this work, you will participate in the development of exceptional technology in high performance computing and ensure product success.

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 team behind Google's groundbreaking innovations, empowering the development of our 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 $132,000-$189,000 + 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

  • Drive development of a leading edge 3D technology platform for custom, high performance ASIC’s and SoC’s, from design through manufacturing, packaging, and test.

  • Optimize digital blocks for performance, power, area, and reliability using physical design and circuit techniques.

  • Define optimal methodologies by investigating performance, power, and area across different technology nodes and implementation techniques.

  • Work with our physical design, technology, circuits, and architecture teams and IP partners in advanced Complementary Metal-Oxide-Semiconductor (CMOS) nodes.

  • Design and build custom circuits at the transistor and gate levels to support physical design and floorplan optimization.

Minimum qualifications

  • PhD degree in Electrical Engineering, Computer Engineering, Computer Science, a related field, or equivalent practical experience.

  • Academic, educational, internship, or project experience with physical design and 3D integration technologies such as 3D-IC, 2.5D, chip stacking, vertical stacking, integrity, or Through-Silicon Vias (TSV).

  • Experience with running industry standard tools for chip design (e.g., from Synopsys, Cadence, or Siemens EDA).

Preferred qualifications

  • Experience with advanced finfet and gate-all-around technology nodes, and enabling physical design flows in these nodes.

  • Experience in delivering optimized digital place-and-route blocks leading to test chip or product tapeouts.

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About Google

Google

Google

Public

Google specializes in internet-related services and products, including search, advertising, and software.

10,001+

Employees

Mountain View

Headquarters

$1,700B

Valuation

Reviews

3.7

25 reviews

Work Life Balance

3.8

Compensation

4.2

Culture

3.4

Career

3.9

Management

2.8

68%

Recommend to a Friend

Pros

Excellent compensation and benefits

Smart and talented colleagues

Great perks and work flexibility

Cons

Management and leadership issues

Bureaucracy and slow processes

Constantly changing priorities and reorganizations

Salary Ranges

63,375 data points

Junior/L3

L3

L4

L5

L6

L7

L8

Mid/L4

Principal/L7

Senior/L5

Staff/L6

Director

Junior/L3 · Data Scientist L3

0 reports

$176,704

total / year

Base

-

Stock

-

Bonus

-

$150,298

$203,110

Interview Experience

9 interviews

Difficulty

3.4

/ 5

Duration

14-28 weeks

Offer Rate

44%

Experience

Positive 0%

Neutral 56%

Negative 44%

Interview Process

1

Application Review

2

Online Assessment/Technical Screen

3

Phone Screen

4

Onsite/Virtual Interviews

5

Team Matching

6

Offer

Common Questions

Coding/Algorithm

System Design

Behavioral/STAR

Technical Knowledge

Product Sense