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求人Google

Silicon RTL Design Engineer, Google Cloud

Google

Silicon RTL Design Engineer, Google Cloud

Google

·

On-site

·

Full-time

·

2w ago

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.

In this role, you will be part of a team developing Application-Specific Integrated Circuit (ASICs) used to accelerate machine learning computation in data centers. You will collaborate with members of architecture, verification, power and performance, physical design to specify and deliver quality designs for next-generation data center accelerators. You will solve technical problems with micro-architecture and practical reasoning solutions, and evaluate design options with complexity, performance, power.

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.

Responsibilities

  • Drive design methodology, libraries, debug, code review in co-ordination with other IP Design Verification (DV) teams and Physical Design teams.

  • Identify and drive power, performance and area of improvements.

  • Participate in design, implementation and integration of chassis and subsystems.

  • Perform RTL coding for Subsystems/SoC integration, function/performance simulation debug, Lint/CDC/FV/UPF checks.

  • Perform quality check flows like Lint, CDC, RDC, VCLP.

Minimum qualifications

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

  • 4 years of experience in ASIC development with Verilog/System Verilog, Very High Speed Integrated Circuit (VHSIC), Hardware Description Language (VHDL), or Chisel.

  • Experience with micro-architecture and designing IPs and subsystems.

  • Experience in one coding/scripting language (e.g., Python, Perl).

Preferred qualifications

  • Experience in System on a Chip (SoC) designs and integration flows.

  • Experience in AI/ML.

  • Knowledge of arithmetic units, bus architectures, processor design, accelerators, or memory hierarchies.

  • Knowledge of high performance and low power design techniques.

総閲覧数

0

応募クリック数

0

模擬応募者数

0

スクラップ

0

Googleについて

Google

Google

Public

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

10,001+

従業員数

Mountain View

本社所在地

$1,700B

企業価値

レビュー

3.7

25件のレビュー

ワークライフバランス

3.8

報酬

4.2

企業文化

3.4

キャリア

3.9

経営陣

2.8

68%

友人に勧める

良い点

Excellent compensation and benefits

Smart and talented colleagues

Great perks and work flexibility

改善点

Management and leadership issues

Bureaucracy and slow processes

Constantly changing priorities and reorganizations

給与レンジ

57,502件のデータ

Junior/L3

L3

L4

L5

L6

L7

L8

Mid/L4

Principal/L7

Senior/L5

Staff/L6

Director

Junior/L3 · Data Scientist L3

0件のレポート

$176,704

年収総額

基本給

-

ストック

-

ボーナス

-

$150,298

$203,110

面接体験

9件の面接

難易度

3.4

/ 5

期間

14-28週間

内定率

44%

体験

ポジティブ 0%

普通 56%

ネガティブ 44%

面接プロセス

1

Application Review

2

Online Assessment/Technical Screen

3

Phone Screen

4

Onsite/Virtual Interviews

5

Team Matching

6

Offer

よくある質問

Coding/Algorithm

System Design

Behavioral/STAR

Technical Knowledge

Product Sense