채용
About the job
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.
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.
Responsibilities
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Manage the supplier quality and reliability for optical circuit switch (OCS) components, from new product introduction (NPI) through end-of-life.
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Lead cross-functional initiatives to ensure the OCS supply chain's technical and operational readiness for mass production.
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Drive supplier selection and qualification by conducting on-site audits and serve as the subject matter expert to influence product roadmaps.
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Resolve critical fleet and factory issues by leading suppliers through root cause and corrective action (RCCA) and failure analysis (FA) processes.
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Develop, implement, and monitor advanced quality plans and process controls (e.g., FMEA, Cpk, etc.) to drive continuous improvement and maintain supplier partnerships.
Minimum qualifications
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Bachelor's degree in Quality Engineering, Electrical Engineering, or equivalent practical experience.
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8 years of experience in quality, reliability or product engineering.
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4 years of experience in OCS manufacturing processes.
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Experience with the manufacturing and test processes, defects, and quality standards for optical components (e.g., lasers, photodetectors, lenses, filters, fiber assemblies, waveguides, ASIC and PCBs with optical interfaces).
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Experience with hardware in industries such as servers, automotive, or aerospace.
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Ability to travel up to 20% of the time as required.
Preferred qualifications
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7 years of experience in supply chain management, procurement, or operations roles within a high-volume, complex manufacturing or technology environment.
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Experience in material readiness, production control, and supplier performance management.
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Experience across all phases of a product life-cycle from prototype to mass production to end-of-life.
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Experience in data-motivated decision-making.
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Ability to manage bills of materials (BOMs) and complex production schedules.
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Excellent investigative thinking, problem-solving, communication and presentation skills, with the ability to communicate status and risks to cross-functional audiences.
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Google 소개

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
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