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Silicon Quality and Reliability Engineer, Google Cloud

Google

Silicon Quality and Reliability Engineer, Google Cloud

Google

·

On-site

·

Full-time

·

1w ago

  • Perform end-to-end electrical and physical failure analysis on Central Processing Unit/Tensor Processing Unit (CPU/TPU) devices from prototype stages through manufacturing.

  • Utilize advanced hardware and software techniques, such as Emission Microscope (EMMI) and Optical Beam Induced Resistance Change (OBIRCH), to localize defects within reasoning and memory blocks.

  • Execute destructive techniques including delayering, cross-sectioning, and high-resolution imaging (e.g., Scanning Electron Microscope (SEM), Transmission Electron Microscope (TEM), Focused Ion Beam (FIB)) to visualize and identify physical defects.

  • Partner with design, product, and foundry teams to interpret failure data and implement actions for design or process improvements.

  • Generate Failure Analysis (FA) reports and develop novel workflows tailored for advanced technology nodes and three-dimensional (3D) packaging architectures.

Be part of a team that pushes boundaries, developing custom silicon solutions that power the future of Google's direct-to-consumer products. You'll contribute to the innovation behind products loved by millions worldwide. Your expertise will shape the next generation of hardware experiences, delivering unparalleled performance, efficiency, and integration.
In this role, you will help to build the System-on-a-chip (So Cs) that power these facilities by driving quality and reliability processes in High Volume Manufacturing (HVM) from an Integrated Circuit perspective. You will partner with cross-functional teams to develop HVM quality and reliability specifications while collaborating with global hardware teams, silicon design, validation, and engineering groups to ensure fleet excellence.

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 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.

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

  • 2 years of experience in semiconductor failure analysis or a related process engineering role.

  • Experience with standard failure analysis lab equipment (e.g., Curve Tracer, Focused Ion Beam (FIB), Scanning Electron Microscope (SEM)).

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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

57,502 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 per 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