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Staff Engineer, Homestack Quality, Search

Google

Staff Engineer, Homestack Quality, Search

Google

·

On-site

·

Full-time

·

1mo ago

Benefits & Perks

Professional development budget

Generous paid time off and holidays

Flexible work arrangements

Competitive salary and equity package

Parental leave

Learning

Flexible Hours

Equity

Parental Leave

Required Skills

TypeScript

PostgreSQL

Node.js

About the job

Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. 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’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. 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.
In Google Search, we're reimagining what it means to search for information – any way and anywhere. To do that, we need to solve complex engineering challenges and expand our infrastructure, while maintaining a universally accessible and useful experience that people around the world rely on. In joining the Search team, you'll have an opportunity to make an impact on billions of people globally.

Responsibilities

  • Focus on quality and ranking of widgets and content selection problems.

  • Build Artificial Intelligence (AI) models, tune features, signals with goals to improve interactions and drive visits to search.

  • Work with core quality teams of Notifications and Discover.

  • Drive roadmap, quality infrastructure, model development and deployment.

Minimum qualifications

  • Bachelor’s degree or equivalent practical experience.

  • 8 years of experience in software development.

  • 5 years of experience with one or more of the following: Speech/audio (e.g., technology duplicating and responding to the human voice), reinforcement learning (e.g., sequential selection making), Machine Learning (ML) infrastructure, or in a related ML field.

  • 5 years of experience in leading ML design and optimizing ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).

  • 5 years of experience in testing, and launching software products.

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.

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

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

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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