Senior Applied Scientist, Shopping Convo Foundations - Pre-purchases Science

Amazon Science; Seattle (WA); On-site; USD 167,000 - 226,000; Full time

Benefits offered by this job

Health insurance

RSUs

401(k) matching

Paid time off

Job summary

Amazon Science in Seattle seeks a Senior Applied Scientist to lead AI/ML innovation for expanding Amazon's product catalogue. You will design and deploy state-of-the-art models, run rigorous experiments, and translate breakthroughs into production-ready solutions while guiding junior scientists.

You will collaborate with ML Engineers and Software Development Engineers to optimize performance, ensure scalability, and deploy low-latency solutions at Amazon scale in a global setting.

Qualifications

• 3+ years building ML models for business applications.
• PhD or MS with 6+ years of applied research experience.
• Experience programming in Java, C++, Python.
• Experience with neural deep learning methods and machine learning.

Responsibilities

• Lead research and development of novel ML approaches for catalogue expansion.
• Design and develop state-of-the-art ML models and conduct rigorous experiments.
• Translate breakthroughs into production-ready solutions and production deployment.
• Guide a team of junior scientists and collaborate with ML Engineers and SDEs.
• Optimize model performance for scalability and low-latency Amazon-scale systems.

Skills

Machine learning

Java / C++ / Python

Deep learning

Education

PhD, or MS + 6+ years applied research

Tools

TensorFlow

scikit-learn

Spark MLLib

MxNet

NumPy

Job description

Description

The Shopping Convo Foundations Team - Pre-purchases Science is looking for an Senior Applied Scientist with expertise in Artificial Intelligence and Machine Learning to drive scientific innovation that expands Amazon's product catalogue. Our goal is to leverage AI/ML solutions to enhance catalogue coverage with high precision.

In this role, you will lead the research and development of novel machine learning approaches to solve complex catalogue expansion and product attribute challenges. You lead the design and develop state-of-the-art ML models, conduct rigorous experimentation, translate scientific breakthroughs into production-ready solutions, and guide a set of junior scientists. You will work closely with ML Engineers and Software Development Engineers to optimize model performance, ensure scalability, and deploy low-latency solutions at Amazon scale.

About The Team

Our team is a horizontal applied science group that works across the full lifecycle of brand and product data extraction and quality. We span seven workstreams — from products sourcing and Brand entitlement, to designing and evaluating extraction strategies for ASINs, offers, and brand attributes at scale, as well as relevance modeling and search. We drive root cause analysis through human-in-the-loop evaluation, improve how catalog data surfaces in search, optimize business metrics tied to data quality, and build brand intelligence capabilities. This cross-cutting scope positions the team as a connective layer across product, engineering, and science — ensuring that improvements in one area compound across the system rather than remain siloed.

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.

Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

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, CA, Santa Clara - 192,200.00 - 260,000.00 USD annually

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