amazon

amazon

Posted via Amazon Jobs

Senior Applied Scientist, ASCS AI Lab Team

Posted Aug 3, 2026

Role at a glance

Salary
$167.1K – $226.1K/yr
Location
Seattle, Washington, United States
Work arrangement
On-site
Employment
Full-time
Education
PhD, or Master's degree

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Role Summary

AI-generated

The Senior Applied Scientist will develop AI research and products for Amazon Selection and Catalog Systems within the AI Lab Team. The role focuses on Generative AI, Agentic AI, LLMs, Diffusion and Flow Models, and other machine learning solutions supporting online shopping experiences.

What You'll Do

  • Design and implement novel AI solutions for Amazon catalog of products
  • Develop and train state-of-the-art LLMs, Diffusion Models, and other Generative AI models
  • Build and deploy autonomous AI Agents in Amazon production ecosystem
  • Scale AI models to handle billions of diverse products across multiple languages and geographies
  • Conduct research in areas such as Autonomous AI Agents, Generative AI, Language Modeling, Multi-modality Computer Vision, Diffusion...
  • Collaborate with cross-functional teams to integrate AI models into Amazon's production ecosystem

Generated from the employer's posting. Verify important details before applying.

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Qualifications

Required

  • 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

  • Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
  • Experience with large scale distributed systems such as Hadoop, Spark etc.

Original job description

Content provided by the employer



We are seeking a Senior Applied Scientist to join our team in developing pioneering AI research, Generative AI, Agentic AI, Large Language Models (LLMs), Diffusion and Flow Models, and other advanced Machine Learning and Deep Learning solutions for Amazon Selection and Catalog Systems, within the AI Lab Team. This role offers a unique opportunity to work on AI research and AI products that will shape the future of online shopping experiences.

Our team operates at the forefront of AI research and development, working on challenges that directly impact millions of customers worldwide. We push the boundaries of AI at both the foundational and application layers. As a Senior Applied Scientist, you will have the chance to experiment with LLMs and deep learning techniques, apply your research to solve real-world problems at an unprecedented scale, and collaborate with experienced scientists to contribute to Amazon's scientific innovation.

Join us in redefining the future of shopping. Your work will directly influence how customers interact with the world's largest online store.

Key job responsibilities
- Design and implement novel AI solutions for Amazon catalog of products
- Develop and train state-of-the-art LLMs, Diffusion Models, and other Generative AI models
- Build and deploy autonomous AI Agents in Amazon production ecosystem
- Scale AI models to handle billions of diverse products across multiple languages and geographies
- Conduct research in areas such as Autonomous AI Agents, Generative AI, Language Modeling, Multi-modality Computer Vision, Diffusion Models, Reinforcement Learning
- Collaborate with cross-functional teams to integrate AI models into Amazon's production ecosystem
- Contribute to the scientific community through publications and conference presentations

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.
- Experience with large scale distributed systems such as Hadoop, Spark etc.

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. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.



USA, WA, Seattle - 167,100.00 - 226,100.00 USD annually
amazon

About the company

amazon

Large Enterprise

Amazon is a global leader in e-commerce and cloud computing, founded in 1994 by Jeff Bezos. Initially starting as an online bookstore, it has since expanded its offerings to include a vast range of products and services, including electronics, fashion, and digital content. With Amazon Web Services (AWS), the company also provides powerful cloud solutions to businesses around the world. Known for its innovation, customer-centric approach, and commitment to operational efficiency, Amazon continues to shape the future of retail and technology, consistently seeking new ways to enhance customer experiences.