Jobs
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Work on spatial/temporal super-resolution video denoising, deblurring, color correction foreground segmentation and video understanding.
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Collaborate with peers and stakeholders through design and code reviews to ensure best practices amongst available technologies (e.g., style guidelines, checking code in, accuracy, testability, and efficiency).
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Contribute to the team's on-going efforts in building a complete understanding of the video quality of experience for Meet users.
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Drive AI/ML development in the video space, collaborating cross-functionally to translate emerging AI/ML innovations into tangible features that provide users with higher-order video communication capabilities.
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Bachelor’s degree or equivalent practical experience.
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5 years of experience with software development in one or more programming languages.
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3 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 decision making), ML infrastructure, or specialization in another ML field.
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3 years of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).
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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
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Bonus
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$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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