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Mechanical Engineer, Cooling System Design, Google Data Centers

Google

Mechanical Engineer, Cooling System Design, Google Data Centers

Google

·

On-site

·

Full-time

·

2w ago

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 Mechanical Engineer within Data Center Technology Systems (DCTS) a multidisciplinary consortium of engineers and architects dedicated to pioneering next-generation data centers. You will assume a pivotal role in the development, analysis, and optimization of the mechanical cooling infrastructure. You will leverage advanced analytical tools to unearth crucial data points that inform the design process for highly efficient mechanical systems. Your fundamental understanding of thermodynamics and fluid flow will guide your analysis of air and waterside systems in the evaluation of data center environments with mission-critical operational requirements. You must be a persuasive and concise communicator, adept at articulating technical concepts across all digital platforms and capable of delivering actionable recommendations to cross-functional engineers and architects to elevate the mechanical systems within our data centers and accelerate the pace of construction.

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 team 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.

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

  • Partner with electrical, networking, and operations teams to resolve interrelated issues and optimize the infrastructure for machine learning fleet demands.

  • Maintain internal design specifications and drawings to ensure all configurations meet the latest global regulations and engineering standards.

  • Lead the development of mechanical systems through computational fluid dynamics modeling, thermal/hydraulic analysis, and pipe sizing to ensure efficiency.

  • Peer-review deliverables from architectural and engineering consultants and manufacturing partners, providing technical direction and escalating issues when necessary.

  • Provide site-level engineering support and manage design change documentation to ensure safe, controlled, and optimized system deployments.

Minimum qualifications

  • Bachelor's degree in Mechanical or Industrial Engineering, related discipline, or equivalent practical experience.

  • 3 years of experience with mechanical infrastructure systems.

  • Experience working with thermodynamics, fluid flow, and heat transfer in cooling or heating systems.

Preferred qualifications

  • Master's degree in Engineering, Business or other relevant field or a professional engineering license.

  • Experience in designing complex modular building scale assemblies, with an understanding of mechanical tolerances and tolerance analysis.

  • Experience in estimating, mechanical design, operation, and commissioning of data center mechanical equipment.

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About Google

Google

Google

Public

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

10,001+

Employees

Mountain View

Headquarters

$1,700B

Valuation

Reviews

3.7

25 reviews

Work-life balance

3.8

Compensation

4.2

Culture

3.4

Career

3.9

Management

2.8

68%

Recommend to a friend

Pros

Excellent compensation and benefits

Smart and talented colleagues

Great perks and work flexibility

Cons

Management and leadership issues

Bureaucracy and slow processes

Constantly changing priorities and reorganizations

Salary Ranges

57,502 data points

Junior/L3

L3

L4

L5

L6

L7

L8

Mid/L4

Principal/L7

Senior/L5

Staff/L6

Director

Junior/L3 · Data Scientist L3

0 reports

$176,704

total per year

Base

-

Stock

-

Bonus

-

$150,298

$203,110

Interview experience

9 interviews

Difficulty

3.4

/ 5

Duration

14-28 weeks

Offer rate

44%

Experience

Positive 0%

Neutral 56%

Negative 44%

Interview process

1

Application Review

2

Online Assessment/Technical Screen

3

Phone Screen

4

Onsite/Virtual Interviews

5

Team Matching

6

Offer

Common questions

Coding/Algorithm

System Design

Behavioral/STAR

Technical Knowledge

Product Sense