Applied Scientist, Alexa Edge AI

Amazon; Toronto; On-site; CAD 80,000 - 120,000; Full time

Job summary

Join a forward-thinking team focused on advancing AI technology in the realm of computer vision and multimodal perception. As an Applied Scientist, you will leverage your deep learning expertise to develop innovative algorithms that enhance the customer experience across various applications. Collaborate with talented engineers and scientists to bring cutting-edge models to production while contributing to a diverse and inclusive workplace. This role offers the opportunity to work with large-scale data and computing resources, making a significant impact on the future of AI technology. If you're passionate about pushing the boundaries of what's possible, this is the perfect opportunity for you.

Qualifications

• PhD or Master's degree with 3+ years in CS, CE, ML or related fields.
• Experience in programming and building models for business applications.

Responsibilities

• Develop novel algorithms and modeling techniques for multimodal models.
• Run experiments and research new algorithms to optimize customer experience.

Skills

Deep Learning

Computer Vision

Java

C++

Python

Algorithm Development

Model Optimization

Education

PhD in Computer Science or related field

Master's degree in Computer Science or related field

Job description

The Alexa Edge AI team under Alexa Ambient Computing Tech Organization is looking for a passionate, talented, and inventive Applied Scientist with a strong deep learning background, to help build industry-leading technology with computer vision, speech and multimodal perception models for various edge applications.

Key job responsibilities

As an Applied Scientist with the Alexa Edge AI team, you will work with talented peers to develop novel algorithms and modeling techniques to advance the state of the art with multimodal models with an emphasis on computer vision. Your work will directly impact our customers in the form of products and services that make use of CV technology. You will leverage Amazon’s heterogeneous data sources and large-scale computing resources to accelerate advances within perception domain.

A day in the life
An Applied Scientist with the Alexa Edge AI team will support science solution design, run experiments, research new algorithms, and find new ways of optimizing the customer experience; while setting examples for the team on good science practice and standards. Besides theoretical analysis and innovation, an Applied Scientist will also work closely with talented engineers and scientists to put algorithms and models into production.

About the team

The Alexa Edge AI team has a mission to deliver best in class, resource efficient multimodal AI models in support of various perception (vision, audio and speech) based applications for devices like Echo Show series within Amazon.

BASIC QUALIFICATIONS

1. PhD, or Master's degree and 3+ years of CS, CE, ML or related field experience
2. 1+ years of building models for business application experience
3. Experience programming in Java, C++, Python or related language
4. Experience developing and implementing deep learning algorithms, particularly with respect to computer vision algorithms

PREFERRED QUALIFICATIONS

1. Experience in Vision Language Models, Audio-Video fusion and multi-modal LLMs
2. Experience with optimizing computer vision models for on-device deployment (pruning, quantization, distillation, etc.)
3. Effective verbal and written communication skills with non-technical and technical audiences.

Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, disability, age, 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 this link for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.