Jobs
We are seeking a talented Applied Scientist to join Amazon's Traffic Engineering organization in developing next-generation bot detection and mitigation capabilities. You will contribute to the scientific development of real-time anomaly detection systems to identify and counter sophisticated automated threats, including LLM-powered agents, protecting Amazon's websites and subsidiaries worldwide.
This is a critical challenge at the intersection of ML and cybersecurity. With GenAI/LLM-powered bots now capable of mimicking human behavior, evading traditional detections, and monetizing attacks, we must revolutionize our approach from reactive to real-time protection. You'll help build ML systems that can detect threats in milliseconds instead of days, protecting Amazon assets and compute while ensuring legitimate bot traffic continues to benefit our business. This role offers the unique opportunity to implement first-of-its-kind real-time behavior-based ML models that will safeguard Amazon's global infrastructure. Your work will directly impact millions of customers by ensuring the integrity and availability of Amazon's digital presence while advancing the state-of-the-art in automated threat detection and response.
- Key job responsibilities
- Implement and optimize ML models for real-time detection of programmatic access patterns and anomalous behaviors
- Support development of new approaches in identifying LLM-based agents and emerging automated threats
- Apply ML/AI techniques to traffic analysis, classification, and automated response systems
- Work with cross-functional teams to implement layered defense strategies
- Contribute to the team's technical implementations and documentation
About the team
Our team is embarking on a journey to develop the next generation of website traffic management software that protects customers experience. Your work will be highly visible and is instrumental in helping Amazon serve record breaking amounts everyday including flagship events such as Prime Day. If you love building high performance software that's focused on best-in-class networking, data processing, security, and leverages AWS technologies, we have the job for you.
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
- Bachelor's degree in Math, Statistics, Computer Science, or related science field, or experience diving into data to discover hidden patterns and of conducting error/deviation analysis
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, Sunnyvale - 171,600.00 - 222,200.00 USD annually
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About Amazon

Amazon
PublicAmazon.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
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3.7
Culture
2.5
Career
2.3
Management
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35%
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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
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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
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Leadership Principles
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