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职位Google

Software Engineer, Data Center Power Modeling

Google

Software Engineer, Data Center Power Modeling

Google

placeSunnyvale, CA, USA

·

On-site

·

Full-time

·

2mo ago

薪酬

$166,000 - $244,000

福利待遇

Healthcare

Equity

Flexible Hours

必备技能

React

TypeScript

PostgreSQL

About the job

Power Modeling team’s mission is to build tools and services to gather and serve accurate power data about how our fleet of data centers are planned and built, from power grid to chips, enabling maximum utilization of infrastructure, software reliability (e.g., Borg and Colossus), and optimal cluster planning. To accomplish this mission, we create highly reliable services, software tools and UIs to model all power topologies of Google’s data centers from the power sub-station to the racks and in-rack devices, which is critical for optimal planning, safe and reliable operation, and optimal infrastructure utilization. Compute and serve the failure domain data needed to avoid correlated failures in Borg job scheduling and Colossus data placement, which is critical for Google’s reliability. Represent accurate hardware power and thermal models, critical for validating rack design, rack placements and maximizing data center power and cooling infrastructure utilization, while staying within deployment constraints.

The US base salary range for this full-time position is $166,000-$244,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.

Responsibilities

  • Develop and manage the Power Topology infrastructure to construct and serve topological data for current and planned data center power graphs.

  • Utilize Power Grab and Power Map to accurately collect and update power topology data by scanning racks and power equipment during data center audits.

  • Maintain Failure Domain services to ensure high availability for Colossus and Borg, enabling intelligent decision-making for global data and job distribution.

  • Maintain applications used by technicians to record power connections feeding racks and in-rack devices.

  • Analyze power utilization of production and ML machines to verify and increase the accuracy of power models.

Minimum qualifications

  • Bachelor’s degree or equivalent practical experience.

  • 5 years of experience in software development.

Preferred qualifications

  • Master's degree or PhD in Computer Science or a related technical field.

  • Experience with Web Applications, Front-End Development, Angular.

  • Familiarity with managing Google specific productions systems.

  • Excellent coding skills in Java, Typescript, Angular, C++ etc.

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关于Google

Google

Google

Public

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

10,001+

员工数

Mountain View

总部位置

$1,700B

企业估值

评价

3.7

25条评价

工作生活平衡

3.8

薪酬

4.2

企业文化

3.4

职业发展

3.9

管理层

2.8

68%

推荐给朋友

优点

Excellent compensation and benefits

Smart and talented colleagues

Great perks and work flexibility

缺点

Management and leadership issues

Bureaucracy and slow processes

Constantly changing priorities and reorganizations

薪资范围

57,502个数据点

Junior/L3

L3

L4

L5

L6

L7

L8

Mid/L4

Principal/L7

Senior/L5

Staff/L6

Director

Junior/L3 · Data Scientist L3

0份报告

$176,704

年薪总额

基本工资

-

股票

-

奖金

-

$150,298

$203,110

面试经验

9次面试

难度

3.4

/ 5

时长

14-28周

录用率

44%

体验

正面 0%

中性 56%

负面 44%

面试流程

1

Application Review

2

Online Assessment/Technical Screen

3

Phone Screen

4

Onsite/Virtual Interviews

5

Team Matching

6

Offer

常见问题

Coding/Algorithm

System Design

Behavioral/STAR

Technical Knowledge

Product Sense