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Posted via Amazon Jobs

Principal Applied Scientist, AWS Data Center Services

Posted Oct 23, 2026

Role at a glance

Job function
AI & Data AI Research & Applied Science
Salary
Not yet verified Check the description for pay details; an amount or pay period has not been verified.
Location
Seattle, Washington, United States Denver, Colorado, United States
Work arrangement
On-site
Experience
Proven track record of delivery Preferred Qualifications 7+ years of industrial experience in predictive modeling and analysis, predictive software development
Education
Basic Qualifications PhD in Machine Learning, Computer Vision, Statistics or in a highly quantitative field.

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Role Summary

AI-generated

The Principal Applied Scientist role on the AWS Data Center Services team works on science for AWS data center problems, including computer vision models for physical infrastructure repair activities and improvements to the certainty, latency, and performance of a generative AI service. The role works backwards from these problems, partners with software development teams to deliver solutions, and owns the lifecycle from research through production deployment.

What You'll Do

  • Select, train, and evolve computer vision models for targeted activities on AWS infrastructure inside data centers.
  • Build smart retrieval algorithms and reduce model hallucination on safety-critical outcomes in the generative AI service.
  • Design experiments to test whether work-order history improves incident traversal accuracy against historical incident data.
  • Turn field engineer incident scenarios into new benchmarks.
  • Prototype cross-discipline reasoning for incidents spanning electrical and cooling systems.
  • Publish results and draft papers.

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

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Qualifications

Required

  • PhD in Machine Learning, Computer Vision, Statistics or in a highly quantitative field
  • Strong Problem solving ability
  • Good skills in Python (or similar language)
  • Strong communication and data presentation skills
  • Proven track record of delivery

Preferred

  • 7+ years of industrial experience in predictive modeling and analysis, predictive software development
  • Experience in Generative AI
  • Publications or presentation in recognized Computer Vision, Machine Learning or Data Mining journals/conferences
  • Experience in mentoring junior team members, and guiding them on machine learning and data modeling applications
  • Experience working with retail or e-commerce data
  • Experience working with distributed systems and device level software

Original job description

Content provided by the employer

Application deadline: Oct 27, 2026

The AWS Data Center Services team is hiring a Principal Applied Scientist to innovate and advance the science behind solutions to problems in the rapidly growing AWS data center space.

These problems range from bespoke computer vision models to support our physical infrastructure functions such as repair activities, to increasing the certainty of decisions made by our generative AI service without sacrificing latency or performance. For example, when a data center technician is triaging a critical electrical event at 2am and alarms cascade in seconds, our AI service has to cross-reference topology, live readings, maintenance history, and design documents within minutes - work that today takes an order of magnitude more time and intervention from a senior engineer.

As a Principal Applied Scientist, you will work backwards from these problems and partner with software development teams to deliver solutions. You will work on problems ranging from selecting, training and evolving computer vision models for targeted activities on AWS infrastructure inside our data centers; to building smart retrieval algorithms, reduce model hallucination on safety-critical outcomes, continually improve latency and performance, and ensure our generative AI service's knowledgeable stays current and the service is constantly getting smarter beyond just knowledge retrieval.

A day in the life
You start the morning reviewing traces from last night’s incident triage. The agent correctly walked the topology to the upstream breaker but missed a recent maintenance change that was the real cause — so you design an experiment: does feeding work-order history into the traversal improve accuracy? You test it against historical incident data. Mid-morning, you review verification traces and catch the agent missing a spec deep in a submittal. After lunch, a field engineer walks you through manually cross-referencing five systems during an incident and you turn their scenario into a new benchmark. In the afternoon, you prototype cross-discipline reasoning: when a cascade spans electrical and cooling, can the lead agent delegate scoped investigations and still hold one coherent hypothesis? You publish results and draft a paper. You own the full lifecycle — research through production deployment.

About the team
Data Center Services is part of AWS Infrastructure Services that owns the design, planning, delivery, and operation of all AWS global infrastructure. In other words, we’re the people who keep the cloud running. We support all AWS data centers and all of the servers, storage, networking, power, and cooling equipment that ensure our customers have continual access to the innovation they rely on. We work on the most challenging problems, with thousands of variables impacting the supply chain - and we’re looking for talented people who want to help.

You’ll join a diverse team of software, hardware, and network engineers, supply chain specialists, security experts, operations managers, and other vital roles. You’ll collaborate with people across AWS to help us deliver the highest standards for safety and security while providing seemingly infinite capacity at the lowest possible cost for our customers. And you’ll experience an inclusive culture that welcomes bold ideas and empowers you to own them to completion.

Basic Qualifications

PhD in Machine Learning, Computer Vision, Statistics or in a highly quantitative field.
Strong Problem solving ability
Good skills in Python (or similar language)
Strong communication and data presentation skills
Proven track record of delivery

Preferred Qualifications

7+ years of industrial experience in predictive modeling and analysis, predictive software development
Experience in Generative AI
Publications or presentation in recognized Computer Vision, Machine Learning or Data Mining journals/conferences
Experience in mentoring junior team members, and guiding them on machine learning and data modeling applications
Experience working with retail or e-commerce data
Experience working with distributed systems and device level software

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, CO, Denver - 198,900.00 - 269,000.00 USD annually
USA, WA, Seattle - 198,900.00 - 269,000.00 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.