Principal Applied Scientist, Ring AI

Amazon; Toronto; On-site; CAD 120,000 - 160,000; Full time

Job summary

A leading technology company in Toronto is seeking a Principal Applied Scientist to focus on computer vision and machine learning innovations. This role requires a PhD and over 10 years of experience in ML applications. The successful candidate will define research directions, develop strategies, and lead full-cycle development efforts. This is an exciting opportunity to make a significant impact on enhancing customer experiences through technology.

Qualifications

• PhD in a relevant technical field is required.
• 10+ years of experience in applying machine learning.
• Experience programming in Java, C++, Python.

Responsibilities

• Define key research directions in Multimodal LLMs and Computer Vision.
• Develop long-term strategies and participate in organizational planning.
• Serve as a key scientific resource in full-cycle development.

Skills

Machine Learning

Computer Vision

Algorithm Design

Programming in Java, C++, Python

Natural Language Processing

Natural Language Processing

Education

PhD in Electrical Engineering, Computer Science, Mathematics, or related field

Job description

Are you a passionate scientist in the computer vision area who is aspired to apply your skills to bring value to millions of customers? Here at Ring, we have a unique opportunity to innovate and see how the results of our work improve the lives of millions of people and make neighborhoods safer.

As a Principal Applied Scientist, you will work with talented peers pushing the frontier of computer vision and machine learning technology to deliver the best experience for our neighbors.

This is a great opportunity for you to innovate in this space by developing highly optimized algorithms that will work at scale. This position requires experience with developing Computer Vision, Multi-modal LLMs and/or Vision Language Models. You will collaborate with different Amazon teams to make informed decisions on the best practices in machine learning to build highly-optimized integrated hardware and software platforms.

Key job responsibilities

• You will be responsible for defining key research directions in Multimodal LLMs and Computer Vision, adopting or inventing new techniques, conducting rigorous experiments, publishing results, and ensuring that research is translated into practice.
• You will develop long-term strategies, persuade teams to adopt those strategies, propose goals and deliver on them.
• You will also participate in organizational planning, hiring, mentorship and leadership development.
• You will serve as a key scientific resource in full-cycle development (conception, design, implementation, testing to documentation, delivery, and maintenance).

Basic Qualifications

• PhD in Electrical Engineering, Computer Science, Mathematics, or a related technical field
• 10+ years of practical work applying ML to solve complex problems experience
• Experience programming in Java, C++, Python or related language
• Experience with leading experienced scientists as well as having a record of developing junior members from academia or industry to a career track in a business environment
• Experience with computer vision, vision language models, deep learning, and/or natural language processing

Preferred Qualifications

• Knowledge of problem solving, algorithm design and complexity analysis
• Experience creating novel algorithms and advancing the state of the art
• Have peer-reviewed scientific contributions in premier journals and conferences

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. 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.