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트렌딩 기업

트렌딩 기업

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채용Google

Power and Signal Integrity Engineer, PhD Graduate

Google

Power and Signal Integrity Engineer, PhD Graduate

Google

·

On-site

·

Full-time

·

1w ago

  • Generate precise electrical models (e.g., S-parameters, SPICE models) for components such as packages, PCBs, and connectors for use in simulations.

  • Simulate high speed interface electrical behavior using HSPICE or other circuit simulators.

  • Execute lab measurements utilizing test equipment like oscilloscopes, Vector Network Analyzers (VNA), Time Domain Reflectometers (TDR), spectrum analyzers to validate simulation outcomes and debug signal and power-related issues on silicon prototypes and boards.

  • Establish design rules and guidelines for optimal signal/power integrity during PCB and package layout, ensuring high production yield and reliability.

  • Document design specifications, analysis results, and validation reports to ensure compliance with standards and for future reference, while collaborating extensively with cross-functional teams, including ASIC architects, digital/analog designers, physical design/layout engineers, and system engineers.

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.
As a Power and Signal Integrity Engineer, you will be responsible for the design and characterization of signal and power integrity of our IC designs. You will design the external electrical interfaces of the device, from their Signal/Power-integrity and electrical usage perspectives and set up methodologies, perform simulations, silicon characterization and correlations to ensure our IC designs meet systems design budgets and achieve the highest performance. You will work with systems architects, ASIC design, systems engineers, and partner cross-functionally with teams and external vendors/partners.

The ML, Systems, & Cloud AI (MSCA) organization at Google designs, implements, and manages the hardware, software, machine learning, and systems infrastructure for all Google services (Search, YouTube, etc.) and Google Cloud. Our end users are Googlers, Cloud customers and the billions of people who use Google services around the world.

We prioritize security, efficiency, and reliability across everything we do - from developing our latest TPUs to running a global network, while driving towards shaping the future of hyperscale computing. Our global impact spans software and hardware, including Google Cloud’s Vertex AI, the leading AI platform for bringing Gemini models to enterprise customers.

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

  • Experience in any signal and power integrity domain of electrical engineering through internships, academic research, or publications.

총 조회수

0

총 지원 클릭 수

0

모의 지원자 수

0

스크랩

0

Google 소개

Google

Google

Public

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

10,001+

직원 수

Mountain View

본사 위치

$1,700B

기업 가치

리뷰

3.7

25개 리뷰

워라밸

3.8

보상

4.2

문화

3.4

커리어

3.9

경영진

2.8

68%

친구에게 추천

장점

Excellent compensation and benefits

Smart and talented colleagues

Great perks and work flexibility

단점

Management and leadership issues

Bureaucracy and slow processes

Constantly changing priorities and reorganizations

연봉 정보

57,502개 데이터

Junior/L3

L3

L4

L5

L6

L7

L8

Mid/L4

Principal/L7

Senior/L5

Staff/L6

Director

Junior/L3 · Data Scientist L3

0개 리포트

$176,704

총 연봉

기본급

-

주식

-

보너스

-

$150,298

$203,110

면접 경험

9개 면접

난이도

3.4

/ 5

소요 기간

14-28주

합격률

44%

경험

긍정 0%

보통 56%

부정 44%

면접 과정

1

Application Review

2

Online Assessment/Technical Screen

3

Phone Screen

4

Onsite/Virtual Interviews

5

Team Matching

6

Offer

자주 나오는 질문

Coding/Algorithm

System Design

Behavioral/STAR

Technical Knowledge

Product Sense