招聘
About the job
Our thirst for technology is a part of everything we do. The Data Center Engineering team takes the physical design of our data centers into the future. Our lab mirrors a research and development department -- cutting-edge strategies are born, tested and tested again. Along with a team of great minds, you take on complex topics like how we use power or how to run state-of-the-art, environmentally-friendly facilities. You're a visionary who optimizes for efficiencies and never stops seeking improvements -- even small changes that can make a huge impact. You generate ideas, communicate recommendations to senior-level executives and drive implementation alongside facilities technicians.
With your technical expertise, you ensure compliance with codes and standards, develop infrastructure improvements and serve as an expert in your specialty (e.g., cooling, electrical).
As a Data Center Systems Engineer within Google's Data Center Technology Systems team, you will analyze power utilization and other dynamics of data center systems, evaluate technology integration options, and develop new strategies to optimize data center efficiency and performance.
The US base salary range for this full-time position is $122,000-$174,000 + 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
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Develop new methods and algorithms to optimize data center efficiency and performance.
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Conduct empirical statistical analysis and modeling of physical variables in data center systems.
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Design, implement, and validate control systems supporting service-level objectives.
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Analyze approaches to manage dynamics of data center electrical and mechanical systems.
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Collaborate across engineering teams to implement new algorithms, strategies, and processes.
Minimum qualifications
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Bachelor's in Engineering, Science, a related field, or equivalent practical experience.
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3 years of experience designing and implementing controls systems and controls modeling.
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Experience with machine learning and construction of algorithms.
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Experience with programming in C, Python, MATLAB, or Shell.
Preferred qualifications
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Master's degree or PhD in Engineering, Science, or a related field.
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Experience with modeling/statistical software such as Tensor Flow, Simulink, R, or MATLAB Machine Learning Toolbox.
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Experience with digital signal processing and time-series analysis.
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Experience with optimization, Linear Programming, and Convex Optimization.
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Experience with dynamic system analysis, feedback control systems (PID Control), and optimal control.
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Ability to work effectively with cross-discipline teams (e.g., structural, civil, IT/Telecom, security, mechanical, architectural) with execellent communication skills.
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关于Google

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
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