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Google
Google

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

Software Engineer, AI Infrastructure

RoleEngineering
LevelMid Level
WorkOn-site
TypeFull-time
Posted3 weeks ago
Apply now
  • Design and develop components of scalable machine learning and agentic AI infrastructure for manufacturing.

  • Maintain and improve existing AI platforms for support of advanced automatic optical inspection.

  • Develop and operate scalable back-end for online machine learning model serving and online inference.

  • Develop advanced data collection back-end and investigative portal for advanced manufacturing insights.

  • Write design documents and participate in design reviews.

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 this role, you will take ownership of improving and scaling our existing Automated Optical Inspection (AOI) systems. This involves optimizing large-scale data pipelines, improving model-serving performance, and ensuring the high reliability of infrastructure that is critical to production. You will be a key contributor to our next-generation initiatives in agentic AI helping to design and build new intelligent systems that can autonomously reason, diagnose failures, and drive operational decisions, directly impacting efficiency and output.

Google's mission is to organize the world's information and make it universally accessible and useful. Our Devices & Services team combines the best of Google AI, Software, and Hardware to create radically helpful experiences for users. We research, design, and develop new technologies and hardware to make our user's interaction with computing faster, seamless, and more powerful. Whether finding new ways to capture and sense the world around us, advancing form factors, or improving interaction methods, the Devices & Services team is making people's lives better through technology.

  • Bachelor's degree in Electrical Engineering, Computer Science, a relevant technical field, or equivalent practical experience.

  • 2 years of experience with software development in one or more programming languages (e.g., C++/C, Java, Python, JavaScript).

  • 1 year of experience with ML infrastructure (e.g., model deployment, model evaluation, model serving, data processing, debugging, fine tuning) or agentic AI development.

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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

Mid/L4

Mid/L4 · Accessibility Analyst

1 reports

$214,500

total per year

Base

$165,000

Stock

-

Bonus

-

$214,500

$214,500

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