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Applied Scientist, End User Messaging, AWS Applied AI Solutions Core Services

Amazon

Applied Scientist, End User Messaging, AWS Applied AI Solutions Core Services

Amazon

Seattle, WA, USA

·

On-site

·

Full-time

·

1w ago

As part of the AWS Applied AI Solutions organization, we're advancing the frontier of trust and safety systems for cloud-based communication services. Our vision is to be the trusted foundation for transforming every business with Amazon AI teammates. Our mission is to deliver turnkey, enterprise-grade foundational AI capabilities that create delightful AI powered solutions. We're building sophisticated AI systems that protect infrastructure from evolving threats while enabling legitimate high-volume users to operate without friction, with messaging services at scale as a key application area.

  • Key job responsibilities
  • Develop advanced machine learning approaches and agentic systems that autonomously adapt to evolving threat patterns across cloud communication services
  • Create behavioral detection models that quickly identify malicious patterns after onboarding rather than creating friction during signup
  • Design intelligent resource allocation algorithms that optimize service delivery based on real-time feedback
  • Develop frameworks operating at scale across diverse usage patterns, analyzing hundreds of thousands of daily active customers
  • Research novel approaches combining AI agents with trust and safety systems to solve complex security problems
  • Collaborate with engineering teams to integrate science components into production systems
  • Conduct rigorous experimentation and establish evaluation frameworks to measure solution performance

A day in the life
As an Applied Scientist, you'll develop fraud detection algorithms and AI-powered security systems while maintaining a clear path to customer impact. You'll investigate novel approaches to behavioral analysis, develop methods for real-time reputation assessment, and validate ideas through rigorous experimentation. You'll collaborate with other scientists and engineers to transform research insights into scalable solutions, work directly with enterprise customers to understand requirements, and help shape the future of cloud security technology.

About the team
Our team is a central science organization supporting multiple product teams across AWS Core Services. We tackle fundamental challenges in AI and machine learning that require novel approaches beyond off-the-shelf solutions. Working at the intersection of machine learning, large language models, and domain-specific applications, we develop practical techniques that advance the state-of-the-art while maintaining a clear path to customer impact. Our team builds deep domain expertise across geospatial intelligence, trust and safety systems, autonomous operations, and other critical areas, collaborating closely with engineering teams to transform research insights into scalable production solutions.

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 in patents or publications at top-tier peer-reviewed conferences or journals
  • 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

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

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About Amazon

Amazon

Amazon

Public

Amazon.com, Inc. is an American multinational technology company engaged in e-commerce, cloud computing, online advertising, digital streaming, and artificial intelligence.

10,001+

Employees

Seattle

Headquarters

Reviews

2.9

10 reviews

Work Life Balance

2.8

Compensation

3.7

Culture

2.5

Career

2.3

Management

2.1

35%

Recommend to a Friend

Pros

Good pay and compensation

Strong benefits package

Flexible scheduling options

Cons

Poor management and leadership

Limited growth and promotion opportunities

High stress and demanding work environment

Salary Ranges

2 data points

Junior/L3

L2

L3

L4

L5

L6

M3

M4

M5

M6

Mid/L4

Principal/L7

Senior/L5

Staff/L6

Director

Junior/L3 · Data Scientist L4

0 reports

$181,968

total / year

Base

-

Stock

-

Bonus

-

$154,672

$209,264

Interview Experience

10 interviews

Difficulty

3.7

/ 5

Duration

21-35 weeks

Offer Rate

20%

Experience

Positive 10%

Neutral 10%

Negative 80%

Interview Process

1

Application Review

2

Recruiter Screen

3

Online Assessment

4

Technical Phone Screen

5

Onsite/Virtual Loop

6

Team Matching

7

Offer

Common Questions

Coding/Algorithm

System Design

Behavioral/STAR

Leadership Principles

Technical Knowledge