Applied Scientist II - Personalization, Customer Intent Science

Amazon Science; Seattle (WA); On-site; USD 143,000 - 193,000; Full time

Benefits offered by this job

Health insurance

RSUs (restricted stock units)

401(k) matching

Paid time off

Parental leave

Job summary

Amazon Science in Seattle, WA is seeking an Applied Scientist to advance scalable ML and AI for recommendations. You will design, implement, and validate models that improve customer experiences and drive business value.

Collaborate with software teams to productionize algorithms, contribute to state-of-the-art research, and help scale experimentation across millions of users.

Qualifications

• 3+ years building models for business applications
• Experience programming in Java, C++, Python
• Experience in algorithms, data structures, numerical optimization, data mining, parallel and distributed computing

Responsibilities

• Use AI/ML to create scalable solutions for business problems.
• Analyze large volumes of Amazon historical data to automate and optimize processes.
• Design, develop and evaluate highly scalable predictive learning models.
• Collaborate with software engineering teams to deploy models and features.
• Establish scalable, automated processes for big data analyses, model development, validation and deployment.
• Research and implement novel ML/statistical approaches.
• Review peer work and provide constructive feedback.

Skills

ML models

Production code

Algorithms

Education

PhD or MS + 4+ years CS/ML

Job description

Description

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.

USA, WA, Seattle - 142,800.00 - 193,200.00 USD annually