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Sr. Software Development Engineer, Ring AI (Edge AI)

Amazon

Sr. Software Development Engineer, Ring AI (Edge AI)

Amazon

Taipei, TPE, TWN

·

On-site

·

Full-time

·

1w ago

Join Ring AI team to revolutionize home security through innovative technologies that seamlessly integrate edge computing and cloud services. Be part of shaping the future of intelligent device solutions that make communities safer and more connected.

  • Key job responsibilities
  • Develop and deploy edge AI solution with focus on computer vision for Ring devices
  • Collaborate with applied science and cloud service teams to create scalable AI architectures
  • Design and implement efficient Edge AI architectures
  • Conduct performance experiments and system optimization research

A day in the life
As a software developer at Ring AI, you will support solution design and development, conduct experiments, and optimize system performance to enhance customer experience. You'll work closely with the Applied Sciences team to improve model performance while collaborating with Cloud Services to design end-to-end system architecture. Through these partnerships, you'll play a key role in advancing our AI solutions.

About the team
We are a collaborative group of technologists passionate about developing intelligent, efficient AI models. Our vision is to create seamless, adaptive technologies that anticipate and respond to user needs. We're committed to pushing the boundaries of what's possible in device intelligence while maintaining a human-centered approach to innovation.

Basic Qualifications

  • 5+ years of non-internship professional software development experience
  • 4+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience
  • Experience as a mentor, tech lead or leading an engineering team
  • Proficient programming skills in C or C++
  • Demonstrated experience developing AI solutions for embedded systems

Preferred Qualifications

  • Bachelor's degree in computer science or equivalent
  • Experience in machine learning applications
  • Knowledge of cloud architecture
  • Experience using English communication skills, both written and verbal, to foster seamless interaction with stakeholders at all levels
  • Experience with computer vision and deep learning frameworks
  • Degree in Computer Science or related technical field
  • Track record of research contributions or open-source AI project involvement

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

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About Amazon

Amazon

Amazon

Public

Amazon.com, Inc. is an American multinational technology company engaged in e-commerce, cloud computing, online advertising, digital streaming, and artificial intelligence.

10,001+

Employees

Seattle

Headquarters

Reviews

2.9

10 reviews

Work Life Balance

2.8

Compensation

3.7

Culture

2.5

Career

2.3

Management

2.1

35%

Recommend to a Friend

Pros

Good pay and compensation

Strong benefits package

Flexible scheduling options

Cons

Poor management and leadership

Limited growth and promotion opportunities

High stress and demanding work environment

Salary Ranges

2 data points

L2

L3

L4

L5

L6

L2 · Data Analyst L2

0 reports

$108,330

total / year

Base

$43,332

Stock

$54,165

Bonus

$10,833

$75,831

$140,829

Interview Experience

10 interviews

Difficulty

3.7

/ 5

Duration

21-35 weeks

Offer Rate

20%

Experience

Positive 10%

Neutral 10%

Negative 80%

Interview Process

1

Application Review

2

Recruiter Screen

3

Online Assessment

4

Technical Phone Screen

5

Onsite/Virtual Loop

6

Team Matching

7

Offer

Common Questions

Coding/Algorithm

System Design

Behavioral/STAR

Leadership Principles

Technical Knowledge