Sr. Applied Scientist, Silicon and Systems Group Edge AI, Edge AI Platform

Amazon; Vancouver; On-site; CAD 150,000 - 230,000; Full time

Job summary

Amazon Devices seeks a Sr. Applied Scientist for the Silicon and Solutions Group Edge AI Team to advance evaluation methods for multimodal language models across our devices. You will explore audio, vision, and language evaluation challenges and help ship robust methods for production use.

The role emphasizes collaboration with engineers and scientists to extend evaluation frameworks, understand model gaps, and improve customer experiences through on-device AI capabilities.

Qualifications

• 3+ years of building machine learning models for business applications.
• 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.

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.

Skills

ML model development

Programming experience

Deep learning experience

Education

PhD or Master's with 6+ years applied research

Tools

Java

C++

Python

Perl

R

scikit-learn

Spark MLLib

MxNet

TensorFlow

NumPy

SciPy

Linux/Unix

Job description

Sr. Applied Scientist, Silicon and Systems Group Edge AI, Edge AI Platform

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.

Silicon and Solutions Group Edge AI Team

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.

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