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Google
Google

Organizing the world's information and making it universally accessible.

Senior Staff Engineer, Storage, AI/ML, Solutions

RoleMachine Learning
LevelStaff
WorkOn-site
TypeFull-time
Posted3 weeks ago
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  • Develop and enhance AI/ML client libraries for storage.

  • Lead the team to design, develop, and tune benchmarks for GCP Storage systems, positioning GCP Storage as the premier solution for AI/ML workloads.

  • Assist key customers in onboarding their AI/ML workloads onto GCP storage.

  • Work closely with cross-functional teams across GCP including Core GCS, File Solutions, GKE, Cloud ML Compute Services (CMCS), and Networking to drive storage innovation for AI/ML.

  • Bachelor’s degree or equivalent practical experience.

  • 8 years of experience in software development.

  • 7 years of experience in building and developing large-scale infrastructure, distributed systems or networks, or with compute technologies, storage, or hardware architecture.

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

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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

10 reviews

4.5

10 reviews

Work-life balance

3.2

Compensation

4.3

Culture

4.1

Career

4.2

Management

3.8

82%

Recommend to a friend

Pros

Great benefits and perks

Innovative and interesting work

Career development and learning opportunities

Cons

High pressure and expectations

Long hours and heavy workload

Fast-paced and overwhelming environment

Salary Ranges

57,503 data points

Junior/L3

L6

L7

L8

Mid/L4

Principal/L7

Senior/L5

Staff/L6

Director

L3

L4

L5

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