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About the job
Google has one of the largest and most powerful computing infrastructures in the world. Your team is responsible for providing the manufacturing capability to deliver this state-of-the-art physical infrastructure. As a Manufacturing Engineer, you evaluate the product designs and create the processes, tools and procedures behind Google's powerful search technology. When vendors build parts for our infrastructure, you're right there alongside ensuring manufacturing processes are repeatable and controlled. You collaborate with Commodity Managers and Design Engineers to determine Google's infrastructure needs and product specifications. Your work ensures the various pieces of Google's infrastructure fit together perfectly and keep our systems humming along smoothly for a seamless user experience.
Through your leadership, you leverage your technical expertise to design and analyze products and related data, develop and improve manufacturing and supportive processes, and provide consultation to vendors, manufacturers, and internal teams. You lead complex projects to completion by managing resources and activities along the way.
The Platforms and Devices team encompasses Google's various computing software platforms across environments (desktop, mobile, applications), as well as our first party devices and services that combine the best of Google AI, software, and hardware. Teams across this area research, design, and develop new technologies to make our user's interaction with computing faster and more seamless, building innovative experiences for our users around the world.
Responsibilities
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Manage and develop multiple teams of engineers and managers. Define, develop, and drive the adoption of cross-functional initiatives that impact multiple product verticals.
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Partner with module suppliers and internal stakeholders to ensure the technical delivery of subsystem modules. Lead technical investigations and root cause analysis for critical failures.
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Embed end-to-end quality as a core muscle by balancing innovation with predictive validation. Achieve manufacturing quality and deliver advanced customer satisfaction.
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Accelerate digital transformation through intelligent systems within manufacturing operations. Pioneer resilient manufacturing through predictive intelligence and automated line architectures.
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Develop alliances with internal engineering teams and external partners. Communicate strategies and lead technical discussions with executive leadership at both Google and our suppliers.
Minimum qualifications
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Bachelor's degree or equivalent practical experience.
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12 years of experience in manufacturing or supplier development and management.
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10 years of experience in people management.
Preferred qualifications
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Master's degree or PhD in Electrical, Mechanical, Industrial, Materials, or a related engineering field.
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Experience with manufacturing technologies and processes.
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Ability to proactively influence the product design process by proposing improvements with associated data.
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Ability to work, influence, and resolve conflicts cross-functionally with internal and external partners.
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Ability to drive significant yield improvements and cost savings through manufacturing solutions.
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About Google

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
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