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Applied Scientist Gen AI - Amazon Advertising, CreativeX
DESCRIPTION
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 team within Amazon Advertising time aims to democratize access to high-quality creatives (audio, images, videos, text) by building AI-driven solutions for advertisers. To accomplish this, we are investing in understanding how best users can leverage Generative AI methods such as latent-diffusion models, large language models (LLM), generative audio (music and speech synthesis), computer vision (CV), reinforced learning (RL) and related.
As an Applied Scientist you will be part of a close-knit team of other applied scientists and product managers, UX and engineers who are highly collaborative and at the top of their respective fields.
We are looking for talented Applied Scientists who are adept at a variety of skills, especially at the development and use of multi-modal Generative AI and can use state-of-the-art generative music and audio, computer vision, latent diffusion or related foundational models that will accelerate our plans to generate high-quality 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 SOTA research to raise the bar within the team.
As an Applied Scientist on this team, you will:
- Drive the invention and development of novel multi-modal agentic architectures and models for the use of Generative AI methods in advertising.
- Work closely and integrate end-to-end proof-of-concept Machine Learning projects that have a high degree of ambiguity, scale and complexity.
- Build interface-oriented systems that use Machine Learning models, perform proof-of-concept, experiment, optimize, and deploy your models into production; work closely with software engineers to assist in productionizing your ML models.
- Curate relevant multi-modal datasets.
- Perform hands-on analysis and modeling of experiments with human-in-the-loop that eg increase traffic monetization and merchandise sales, without compromising the shopper experience.
- Run A/B experiments, gather data, and perform statistical analysis.
- Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving.
- Mentor and help recruit Applied Scientists to the team.
- Present results and explain methods to senior leadership.
- Willingness to publish research at internal and external top scientific venues.
- Write and pursue IP submissions.
Key job responsibilities
This role is focused on developing new multi-modal Generative AI methods to augment generative imagery and videos. You will develop new multi-modal paradigms, models, datasets and agentic architectures that will be at the core of advertising-facing tools that we are launching. You may also work on development of ML and GenAI models suitable for advertising. You will conduct literature reviews to stay on the SOTA of the field. You will regularly engage with product managers, UX designers and engineers who will partner with you to productize your work.
For reference see our products: Enhanced Video Generator, Creative Agent and Creative Studio.
A day in the life
On a day-to-day basis, you will be doing your independent research and work to develop models, you will participate in sprint planning, collaborative sessions with your peers, and demo new models and share results with peers, other partner teams and leadership.
About the team
The team is a dynamic team of applied scientists, UX researchers, engineers and product leaders. We reside in the Creative X organization, which focuses on creating products for advertisers that will improve the quality of the creatives within Amazon Ads.
We are open to hiring candidates to work out of one of the following locations:
UK (London), USA (Seattle).
BASIC QUALIFICATIONS
- Experience researching, publishing and or developing multi-modal Generative AI systems.
- PhD, or Master's degree and several years of experience of CS, CE, ML or related field experience
- Experience with data curation and creation.
- Programming experience in Java, C++, Python or related ML language.
PREFERRED QUALIFICATIONS
- Advanced degree in Computer Science, Mathematics, Statistics, Economics, or related quantitative field.
- Published relevant research work in academic conferences (e.g. CVPR, ICCV, ECCV, NEURIPS, etc) or industry circles.
- Effective verbal and written communication skills with non-technical and technical audiences.
- Experience working with large real-world data sets and designing scalable models from big data.
- Thinks strategically, but stays on top of tactical execution.
- Exhibits excellent business judgment; balances business, product, and technology very well.
- Familiarity with computational advertising.
Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice ( to know more about how we collect, use and transfer the personal data of our candidates.
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 for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
