Artificial Intelligence jobs in Canada

Amazon Devices is an inventive research and development company that designs and engineer high-profile devices like Echo, Fire Tablets, Fire TV, and other consumer devices. We are looking for exceptional scientists to join our Applied Science team to advance the state-of-the-art in developing efficient multimodal language models across our product portfolio. Through close hardware-software integration, we design and train models for resource efficiency across the hardware and software tech stack.

The Silicon and Solutions Group Edge AI team is looking for a talented Applied Scientist who will develop new evaluation methods for multimodal language models and agents for our devices, including audio and vision experiences.

Key job responsibilities
Collaborate with cross-functional engineers and scientists to advance the state of the art in multimodal model evaluations for devices, including audio, images, and videos
Invent and validate reliability for novel automated evaluation methods for perception tasks, such as fine-tuned LLM-as-judge
Develop and extend our evaluation framework(s) to support expanding capabilities for multimodal language models
Analyze large offline and online datasets to understand model gaps, develop methods to interpret model failures, and collaborate with training teams to enhance model capabilities for product use cases
Work closely with other scientists, compiler engineers, data collection, and product teams to advance evaluation methods.

A day in the life
As a Sr. Applied Scientist with the Silicon and Solutions Group Edge AI team, you'll contribute to innovative methods for evaluating new product experiences and discover ways to enhance our model capabilities and enrich our customer experiences. You'll have opportunities to collaborate across teams of engineers and scientists to bring algorithms and models to production.

About the team
Our Edge AI science team brings together our unique skills and experiences to deliver state-of-the-art multimodal AI models that enable new experiences on Amazon devices.

BASIC QUALIFICATIONS

• 3+ years of building machine learning models for business application experience
• PhD, or Master's degree and 6+ years of applied research experience
• Experience programming in Java, C++, Python or related language
• Experience with neural deep learning methods and machine learning

PREFERRED QUALIFICATIONS

• Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
• Knowledge of programming languages such as C/C++, Python, Java or Perl
• Experience with Linux/Unix operating systems
• Experience in professional software and systems development

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.

The base salary range for this position is listed below. As a total compensation company, Amazon's package may include other elements such as sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon offers comprehensive benefits including health insurance (medical, dental, vision, prescription, basic life & AD&D insurance), Registered Retirement Savings Plan (RRSP), Deferred Profit Sharing Plan (DPSP), paid time off, and other resources to improve health and well-being. We thank all applicants for their interest, however only those interviewed will be advised as to hiring status.

CAN, BC, Vancouver - 195,900.00 - 327,200.00 CAD annually