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Applied Scientist II, Personalization

Amazon

Applied Scientist II, Personalization

Amazon

Seattle, WA, USA

·

On-site

·

Full-time

·

3w ago

Compensation

$142,800 - $193,200

Benefits & Perks

Healthcare

401(k)

Equity

Paid Time Off

Parental Leave

Mental Health

Healthcare

401k

Equity

Parental Leave

Mental Health

Required Skills

Machine Learning

Python

Java

C++

Our team is part of Amazon’s Personalization organization, a high-performing group that leverages Amazon’s expertise in machine learning, big data, distributed systems, and user experience design to deliver the best shopping experiences for our customers. We run global experiments and our work has revolutionized e-commerce with features such as "Keep shopping for", “Customers who bought this item also bought”, and “Frequently bought together” among others.

We are building the next generation of personalized shopping experiences at Amazon through deep understanding of our customer's intent and our product catalog. We aim to create an experience akin to that of a talented personal shopping assistant — a partner that is knowledgeable, understands your preferences, and helps you find the right solution for your needs. We hope you will join us!

Key job responsibilities
As an Applied Scientist on the team you will be working on ways to help customers find the right products on their shopping journey.

You will hone your skills in areas such as Multimodal LLM post-training and cross-modal vision-language reasoning, while building scalable, agentic industry-grade systems.

To be highly successful in this role, the following background is preferred (or expected to be ramped up quickly):

  • A strong Computer Vision foundation
  • Familiarity with multimodal encoders, with hands-on experience training multimodal models
  • End-to-end ML pipeline experience, spanning data curation, model training, and production deployment
  • Experience with LLMs, particularly using LLM-as-a-judge for synthetic data generation
  • Experience with online experimentation, including experiment setup and post-analysis
  • Expertise in multimodal domain generalization is a strong plus

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 programming in Java, C++, Python or related language

Preferred Qualifications

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

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