Demo

Applied Scientist II, Core Search

Amazon Science
Seattle, WA Full Time
POSTED ON 5/24/2026
AVAILABLE BEFORE 6/22/2026
Description

The Amazon Search team creates customer-focused search solutions and technologies. Whenever a customer visits an Amazon site worldwide and types in a query or browses through product categories, Amazon Product Search services go to work. We design, develop, and deploy high performance, fault-tolerant distributed search systems used by millions of Amazon customers every day.

Search Autocomplete and Navigation focuses on helping customers express their shopping intent and navigate search results more effectively. In this role, you will invent universally applicable signals and algorithms to improve suggestion generation, recommendations, and ranking, using LLMs and ML techniques. The improvements you make will help hundreds of millions of customers find the right products faster, from the first keystroke through search result refinement. You will work on problems such as fine-tuning large language models for real-time suggestion generation under strict latency constraints, personalizing recommended content to individual customers, building evaluation frameworks for model selection, and designing data-driven guardrails for LLM-generated content. The work will span the whole development pipeline, including data analysis, evaluation system design, prototyping, A/B testing, and creating production-level systems.

Key job responsibilities

Your Responsibilities Include But Not Limited To

  • Analyze the data and metrics resulting from traffic into Amazon's product search service.
  • Design, build, and deploy effective and innovative ML and LLM solutions to improve search experiences.
  • Evaluate the proposed solutions via offline benchmark tests as well as online A/B tests in production.
  • Publish and present your work at internal and external scientific venues in the fields of ML/NLP/IR.

Basic Qualifications

  • 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 using Unix/Linux
  • Experience in professional software development
  • Experience in state-of-the-art deep learning models architecture design and deep learning training and optimization and model pruning
  • Experience building machine learning models or developing algorithms for business application

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

Salary.com Estimation for Applied Scientist II, Core Search in Seattle, WA
$121,149 to $151,516
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