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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.
As a SoC Vision Architect in Google’s Silicon team, you will be at the heart of defining the hardware that powers the next-generation of Google’s products. You will bridge the gap between AI research and physical silicon, architecting the Image Signal Processor (ISP), CODECS and the pixel data path. You will deliver unparalleled image quality while staying within the tight Power, Performance, and Area (PPA) constraints. You will participate in the concept, architecture, documentation, and implementation of a new product.
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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Define a flexible imaging pipeline hardware architecture, from the sensor interface (e.g., Mobile Industry Processor Interface (MIPI)) through the ISP, the encoder/decoder, scaling and memory output.
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Partner with Google research to transform advanced computational imaging algorithms into high-efficiency hardware logic.
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Conduct trade-off analyses between power, performance, and silicon area to meet thermal envelopes and current limitations.
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Influence external executive vendor roadmaps, ensuring deep co-optimization between their future products and Google’s custom silicon.
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Lead collaboration across Architecture, Register-Transfer Level (RTL), Physical Design and Validation teams.
Minimum qualifications
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Bachelor's degree in Electrical Engineering, Computer Engineering, or equivalent practical experience.
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15 years of experience in SoC architecture, specifically focusing on imaging (JPEG), video (H.264, H.265, AV1) and Image Signal Processor (ISP).
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Experience in Complementary Metal Oxide Semiconductor (CMOS) image sensor architecture.
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Experience in writing architecture specifications.
Preferred qualifications
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Master’s degree or PhD in Electrical Engineering, Computer Engineering, or a related field.
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Experience working with various Software Driver teams.
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Familiarity with deploying neural networks on specialized hardware (e.g., Neural Processing Units (NPUs)/TPUs) for imaging tasks (e.g., AI-based denoising or super-resolution).
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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
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Junior/L3 · Data Scientist L3
0개 리포트
$176,704
총 연봉
기본급
-
주식
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보너스
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$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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