Applied Scientist II, Creative X - RAPID

Amazon logo

Amazon

full-time

Posted: September 14, 2025

Number of Vacancies: 1

Job Description

About Amazon Advertising:Amazon Advertising operates at the intersection of eCommerce and advertising, offering a rich array of digital display advertising solutions with the goal of helping our customers find and discover anything they want to buy. We help advertisers of all types to reach Amazon customers on Amazon.com, across our other owned and operated sites, on other high quality sites across the web, and on millions of mobile devices. We start with the customer and work backwards in everything we do, including advertising. If you’re interested in joining a rapidly growing team working to build a unique, world-class advertising group with a relentless focus on the customer, you’ve come to the right place.About our team:Our team, CreativeX optimizations, is responsible for tailoring the visual experience of ads to each context in real time. To accomplish this, we are investing in latent-diffusion models, large language models (LLM), reinforced learning (RL), Computer Vision, and related methods.Key job responsibilitiesWe are looking for talented Applied Scientists who are adept at a variety of skills, especially with reinforcement learning and recommendations, and familiarity with LLMs, latent diffusion, or related foundational models that will accelerate our plans to dynamically optimize ad creatives on behalf of advertisers. Every member of the team is expected to build customer (advertiser) facing features, contribute to the collaborative spirit within the team, publish, patent, and bring state-of-the-art research to raise the bar within the team.

Locations

  • United States, WA, Seattle, Seattle, WA, United States
  • United States, NY, New York, New York, NY, United States

Salary

Salary not disclosed

Estimated Salary Rangehigh confidence

180,000 - 280,000 USD / yearly

Source: ai estimated

* This is an estimated range based on market data and may vary based on experience and qualifications.

Skills Required

  • - PhD, or Master's degree and 3+ years of CS, CE, ML or related field experienceintermediate
  • - 3+ years of building models for business application experienceintermediate
  • - Experience programming in Java, C++, Python or related languageintermediate
  • - Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computingintermediate

Required Qualifications

  • - PhD, or Master's degree and 3+ years of CS, CE, ML or related field experience (experience, 3 years)
  • - 3+ years of building models for business application experience (experience, 3 years)
  • - Experience programming in Java, C++, Python or related language (experience)
  • - Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing (experience)

Preferred Qualifications

  • - Experience using Unix/Linux (experience)
  • - Experience in professional software development (experience)
  • - Experience building machine learning models or developing algorithms for business application (experience)
  • Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $136,000/year in our lowest geographic market up to $223,400/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site. (experience)

Responsibilities

  • We are looking for talented Applied Scientists who are adept at a variety of skills, especially with reinforcement learning and recommendations, and familiarity with LLMs, latent diffusion, or related foundational models that will accelerate our plans to dynamically optimize ad creatives on behalf of advertisers. Every member of the team is expected to build customer (advertiser) facing features, contribute to the collaborative spirit within the team, publish, patent, and bring state-of-the-art research to raise the bar within the team.

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operations-team-applied-scienceadvertising.team-applied-scienceapplied.aiamazon.artificial-intelligenceMachine Learning Science

Applied Scientist II, Creative X - RAPID

Amazon logo

Amazon

full-time

Posted: September 14, 2025

Number of Vacancies: 1

Job Description

About Amazon Advertising:Amazon Advertising operates at the intersection of eCommerce and advertising, offering a rich array of digital display advertising solutions with the goal of helping our customers find and discover anything they want to buy. We help advertisers of all types to reach Amazon customers on Amazon.com, across our other owned and operated sites, on other high quality sites across the web, and on millions of mobile devices. We start with the customer and work backwards in everything we do, including advertising. If you’re interested in joining a rapidly growing team working to build a unique, world-class advertising group with a relentless focus on the customer, you’ve come to the right place.About our team:Our team, CreativeX optimizations, is responsible for tailoring the visual experience of ads to each context in real time. To accomplish this, we are investing in latent-diffusion models, large language models (LLM), reinforced learning (RL), Computer Vision, and related methods.Key job responsibilitiesWe are looking for talented Applied Scientists who are adept at a variety of skills, especially with reinforcement learning and recommendations, and familiarity with LLMs, latent diffusion, or related foundational models that will accelerate our plans to dynamically optimize ad creatives on behalf of advertisers. Every member of the team is expected to build customer (advertiser) facing features, contribute to the collaborative spirit within the team, publish, patent, and bring state-of-the-art research to raise the bar within the team.

Locations

  • United States, WA, Seattle, Seattle, WA, United States
  • United States, NY, New York, New York, NY, United States

Salary

Salary not disclosed

Estimated Salary Rangehigh confidence

180,000 - 280,000 USD / yearly

Source: ai estimated

* This is an estimated range based on market data and may vary based on experience and qualifications.

Skills Required

  • - PhD, or Master's degree and 3+ years of CS, CE, ML or related field experienceintermediate
  • - 3+ years of building models for business application experienceintermediate
  • - Experience programming in Java, C++, Python or related languageintermediate
  • - Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computingintermediate

Required Qualifications

  • - PhD, or Master's degree and 3+ years of CS, CE, ML or related field experience (experience, 3 years)
  • - 3+ years of building models for business application experience (experience, 3 years)
  • - Experience programming in Java, C++, Python or related language (experience)
  • - Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing (experience)

Preferred Qualifications

  • - Experience using Unix/Linux (experience)
  • - Experience in professional software development (experience)
  • - Experience building machine learning models or developing algorithms for business application (experience)
  • Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $136,000/year in our lowest geographic market up to $223,400/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site. (experience)

Responsibilities

  • We are looking for talented Applied Scientists who are adept at a variety of skills, especially with reinforcement learning and recommendations, and familiarity with LLMs, latent diffusion, or related foundational models that will accelerate our plans to dynamically optimize ad creatives on behalf of advertisers. Every member of the team is expected to build customer (advertiser) facing features, contribute to the collaborative spirit within the team, publish, patent, and bring state-of-the-art research to raise the bar within the team.

Target Your Resume for "Applied Scientist II, Creative X - RAPID"

Get personalized recommendations to optimize your resume specifically for Applied Scientist II, Creative X - RAPID. Our AI analyzes job requirements and tailors your resume to maximize your chances.

Keyword optimization
Skills matching
Experience alignment

Check Your ATS Score for "Applied Scientist II, Creative X - RAPID"

Find out how well your resume matches this job's requirements. Our Applicant Tracking System (ATS) analyzer scores your resume based on keywords, skills, and format compatibility.

Instant analysis
Detailed feedback
Improvement tips

Documents

Tags & Categories

operations-team-applied-scienceadvertising.team-applied-scienceapplied.aiamazon.artificial-intelligenceMachine Learning Science