Applied Scientist II - Personalization, Customer Intent Science

Amazon; San Francisco, Northern (CA, KY); Hybrid; USD 143,000 - 193,000; Full time

Job summary

Amazon's Applied Scientist II - Personalization, Customer Intent Science focuses on building scalable machine learning models to enhance customer shopping experiences. You will work with massive datasets to improve recommendations, with close collaboration with software engineers to productionize algorithms.

The role emphasizes innovation in generative AI/LLMs, deep learning models, and advanced analytics for Amazon's Personalization platform, with opportunities to influence millions of

Qualifications

• 3+ years of building models for business applications.
• PhD, or Master’s with 4+ years in CS/CE/ML.
• Experience programming in Java, C++, Python.

Responsibilities

• Use AI/ML to create scalable solutions for business problems.
• Analyze large volumes of historical data to automate and optimize processes.
• Design, develop and evaluate scalable models for predictive learning.
• Collaborate with software engineers to productionize models.
• Establish scalable data analysis, model development, validation and implementation processes.
• Research novel ML/statistical approaches and review peer work.

Skills

ML modeling

Big data

Distributed computing

Software engineering

Education

PhD or Master’s in CS/CE/ML

Tools

Java

C++

Python

Job description

Applied Scientist II - Personalization, Customer Intent Science

Job ID: 10496447 | Amazon.com Services LLC

Are you interested in big data, Machine Learning, and building recommendation services using Generative AI? If so, Amazon's Personalization team might be the right place for you.

Key job responsibilities

• Use AI and machine learning to create scalable solutions for business problems.
• Analyze and extract relevant information from large amounts of Amazon's historical business data to help automate and optimize key processes.
• Design, develop and evaluate highly scalable models for predictive learning.
• Work closely with software engineering teams to drive model implementations and new feature creations.
• Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation
• Research and implement novel machine learning and statistical approaches
• Review peer work and provide feedback

A day in the life

You are an Applied Scientist who loves big data and passionate about improving customer shopping experience by inventing and applying state-of-art technologies (e.g., LLMs/SLMs, Machine Learning, Natural Language Processing, and Computer Vision) to build the next-generation product recommendation engine for Amazon. You have an entrepreneurial spirit, know how to deliver, are deeply technical and highly innovative. You work closely with software engineers to put algorithms into production. You also work in partnership with teams across Amazon to create enormous benefits for our customers.

About the team

We are part of Amazon’s Personalization organization, a high-performing group with a huge impact on hundreds of millions of customers, innovating at the intersection of customer experience, machine learning, and large-scale distributed systems. We run global experiments and our work has revolutionized e-commerce with features such as "Compare with similar items", "Keep Shopping For", “Customers who bought this item also bought”, and, “Frequently bought together” among others.

Basic Qualifications

• 3+ years of building models for business application experience
• PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
• Experience programming in Java, C++, Python or related language
• Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing

Preferred Qualifications

• Experience with generative deep learning models applicable to the creation of synthetic humans like CNNs, GANs, VAEs and NF
• Experience applying theoretical models in an applied environment
• Hold patents and/or published in top-tier AI/ML venues (conferences and/or journals).

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 .

Preferred Qualifications

• Experience with generative deep learning models applicable to the creation of synthetic humans like CNNs, GANs, VAEs and NF
• Experience applying theoretical models in an applied environment
• Hold patents and/or published in top-tier AI/ML venues (conferences and/or journals).

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 (RSU). 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 - 142,800.00 - 193,200.00 USD annually

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