Sr. Manager, Applied Science, GenAI, Amazon Advertising - Creative X

Amazon; New York (NY); On-site; USD 241,000 - 326,000; Full time

Benefits offered by this job

Health insurance

RSU equity

401(k) matching

Paid time off

Job summary

Amazon Advertising seeks leaders to own the scientific direction for creative quality assessment, content moderation, and multimodal understanding. You will manage and grow a team of applied scientists, driving end-to-end programs and accountable production models across complex domains.

The role emphasizes developing evaluation benchmarks, applying advanced CV/vision-language approaches, and collaborating with product and engineering teams to scale impactful solutions.

Qualifications

• 5+ years managing applied science or ML teams, incl. 2+ years with managers.
• 7+ years applied science in CV, multimodal understanding, or content moderation.
• Experience delivering production ML models for content understanding, quality assessment, or safety and moderation.
• PhD, or Master’s +7 years in CS/CE/ML or related field.

Responsibilities

• Own the scientific direction for creative quality assessment, content moderation and trust and safety, evaluation and benchmarking, and multimodal content understanding.
• Directly lead a team of applied scientists while managing subordinate leads and managers as the portfolio grows.
• Drive end-to-end applied science programs with high ambiguity, scale, and complexity; be accountable for production models.
• Advance the science of evaluation by defining metrics for creative quality, safety, and brand compliance and build benchmarks.
• Research and apply new approaches in computer vision, vision-language models, and multimodal understanding.
• Recruit, mentor, and grow high-performing scientists and managers, raising the hiring and technical bar.
• Establish planning, design reviews, and cross-functional partnership with product and engineering.

Skills

Team leadership

Applied science leadership

ML model development

Strategic thinking

Education

PhD

Master's degree in CS/CE/ML

Advanced degree in quantitative field

Job description

Amazon Advertising is one of Amazon's fastest growing and most profitable businesses. Amazon's advertising portfolio helps merchants, retail vendors, and brand owners succeed via native advertising, which grows incremental sales of their products sold through Amazon. The primary goals are to help shoppers discover new products they love, be the most efficient way for advertisers to meet their business objectives, and build a sustainable business that continuously innovates on behalf of customers. Our products and solutions are strategically important to enable our Retail and Marketplace businesses to drive long-term growth. We deliver billions of ad impressions and millions of clicks and break fresh ground in product and technical innovations every day.

The Creative X org within Amazon Advertising builds the science that decides what is in an ad creative and whether that creative is good, safe, and on-brand. As advertisers and our own generative tools produce creative assets at massive scale, the hard problem shifts from making content to understanding it: scoring quality and aesthetics, catching policy and safety violations before they reach a customer, extracting structured meaning from images and video, and measuring whether a creative meets the bar. We work across computer vision, vision-language models, multimodal understanding, content moderation and trust and safety, and evaluation science. The models this team builds run in production as the quality and safety layer across the entire creative lifecycle, from the moment an asset is generated or uploaded through to what advertisers and shoppers ultimately see.

Key job responsibilities

• Own the scientific direction for creative quality assessment, content moderation and trust and safety, evaluation and benchmarking, and multimodal content understanding.
• Directly lead a team of applied scientists while managing and developing subordinate leads and managers as the portfolio grows across understanding sub-domains.
• Drive end-to-end applied science programs with high ambiguity, scale, and complexity, and be accountable for the resulting models in production.
• Advance the science of evaluation: define how we measure creative quality, safety, and brand compliance, and build the benchmarks and metrics the broader org relies on.
• Research and apply new approaches in computer vision, vision-language models, and multimodal understanding, including quality and aesthetics scoring, safety classification, attribute and metadata extraction, and brand and logo detection.
• Recruit, mentor, and grow high-performing applied scientists and science managers, and raise the hiring and technical bar for the team.
• Establish team mechanisms for planning, document and design reviews, and cross-functional partnership with product and engineering.

Basic Qualifications

• 5+ years experience managing applied science or machine learning teams, including 2+ years managing other managers or team leads.
• 7+ years applied science experience in computer vision, multimodal understanding, or content moderation and trust and safety.
• Experience delivering production machine-learning models for content understanding, quality assessment, or safety and moderation.
• PhD, or Master's degree and 7+ years experience in CS, CE, ML, or a related field.

Preferred Qualifications

• Advanced degree in Computer Science, Mathematics, Statistics, Economics, or a related quantitative field.
• Experience building or scaling a science organization across multiple sub-domains as a manager of managers.
• Published research in academic conferences or industry venues in computer vision, multimodal learning, or content understanding.
• Depth in one or more of: computer vision, vision-language models, content moderation and trust and safety, quality and aesthetics assessment, evaluation and benchmarking methodology, metadata and attribute extraction, or similarity and retrieval.
• Experience building large-scale machine-learning models and infrastructure from large, real-world datasets.
• Effective verbal and written communication with technical and non-technical audiences.
• Thinks strategically while staying on top of tactical execution, and exhibits excellent business judgment balancing product, science, and operational trade-offs.

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, NY, New York - 240,600.00 - 325,500.00 USD annually
• USA, WA, SEATTLE - 218,800.00 - 295,900.00 USD annually

Company

Amazon.com Services LLC

Job ID: A10559036