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Benefits and perks
•Parental Leave
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Required skills
React
JavaScript
Node.js
About the job
Be part of a team that pushes boundaries, developing custom silicon solutions that power the future of Google's direct-to-consumer products. You'll contribute to the innovation behind products loved by millions worldwide. Your expertise will shape the next generation of hardware experiences, delivering unparalleled performance, efficiency, and integration.
As a System Architect, you will play a pivotal role in optimizing Google’s SoC performance for demanding AI and Android applications. You will drive the hardware strategy for the Pixel portfolio, leading the technical definition of future mobile and emerging concepts. By mapping desired user experiences to specific system workloads, you drive the hardware strategy from the ground up. You are responsible for establishing the compute topology and determining the optimal execution of workloads to ensure seamless end-to-end performance. You’ll collaborate with system performance and software teams to plan and conduct workload performance analysis, debug performance bottlenecks and project performance at various design phases. As the product moves into the productization phase, you will act as a technical anchor for the engineering teams. Your role involves validating architectural projections, supporting execution, and influencing key software and product feature decisions. You will remain involved at every critical checkpoint, ensuring the final product meets its power, performance and area goals.
Responsibilities
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Advocate for a holistic system design by owning the end-to-end architecture, balancing compute distribution and data movement to align performance and power with user needs.
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Lead deep-dive architectural investigations to identify bottlenecks and inefficiencies in current and future designs. Propose and validate innovative hardware-software co-optimization strategies that push the boundaries of system performance and power. Explore emerging technologies and architectural paradigms to define new opportunities for compute efficiency and feature enablement.
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Author comprehensive system architecture specifications that map end-to-end data flows. You will clearly articulate how individual system components interact to deliver targeted user experiences.
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Design and implement advanced system-level modeling frameworks and methodologies to accurately forecast power, performance and area. Use these projections to drive critical software optimizations and define the architectural specifications for next-generation hardware.
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Drive post-silicon power characterization, optimization, and productization initiatives.
Minimum qualifications
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Bachelor's degree in Electrical Engineering, Computer Engineering, Computer Science, a related field, or equivalent practical experience.
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10 years of experience in Convolutional Neural Network (CNN) data flows and their execution on Neural Processing Units (NPUs).
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Experience in full software stack, including compilers, runtimes, and GPU/media processing pipelines.
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Experience in Linux kernel scheduling and advanced power management strategies.
Preferred qualifications
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Master's degree or PhD in Electrical Engineering, Computer Engineering or Computer Science, with an emphasis on computer architecture.
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Knowledge of ML benchmarks and workloads.
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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
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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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