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Senior Staff Software Engineer, Machine Installation

Google

Senior Staff Software Engineer, Machine Installation

Google

placeSunnyvale, CA, USA

·

On-site

·

Full-time

·

1mo ago

Compensation

$248,000 - $349,000

Benefits & Perks

Team events and activities

Comprehensive health, dental, and vision insurance

Generous paid time off and holidays

Competitive salary and equity package

401(k) matching

Parental leave

Healthcare

Equity

Parental Leave

Required Skills

Python

JavaScript

PostgreSQL

About the job

Google Cloud's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google Cloud's needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. You will anticipate our customer needs and be empowered to act like an owner, take action and innovate. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.

The machine installation team, owns the services that deploy, protect, configure, and schedule the foundational layers of software, including firmware, operating systems, and the components underlying Borg and Google Cloud Platform, for Google’s planet-scale fleet of production machines.

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 force 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 $248,000-$349,000 + 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

  • Provide technical leadership on high-impact projects.

  • Influence and coach a distributed team of engineers.

  • Lead and optimize our machine installation processes for both software and firmware on some of the most multinode compute, storage, and Machine Learning (ML) acceleration platforms in the world.

  • Work closely with our diagnostic, quality, supply chain, and hardware teams to ensure that hardware problems that prevent installation from proceeding properly have sufficient telemetry to guide our operations teams to the correct hardware repair to restore the machines capacity.

  • Collaborate with our software and firmware teams to ensure that our installation reliability and performance allows us to meet critical SLO's with our internal and external customers.

Minimum qualifications

  • Bachelor's degree or equivalent practical experience.

  • 8 years of experience programming in C++.

  • 5 years of experience with design and architecture; and testing/launching software products.

  • Experience in software architecture, software development, Linux, testing, C++, and Linux Administration.

Preferred qualifications

  • Master’s degree or PhD in Engineering, Computer Science, or a related technical field.

  • 8 years of experience with data structures and algorithms.

  • 5 years of experience in a technical leadership role leading project teams and setting technical direction.

  • 3 years of experience working in a matrixed organization involving cross-functional, or cross-business projects.

  • Experience in network technologies and protocols related to unattended software installation and remote server management.

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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

63,375 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 / 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