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Gen AI Audio-Video Applied Scientist, CreativeX

Job ID: 2474319 | Amazon Advertising LLC


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 team within Amazon Advertising aims to democratize access to high-quality creatives (audio, images, videos, description) by building AI-driven solutions for advertisers. To accomplish this, we are investing in latent-diffusion models, large language models (LLM), generative audio (music and speech synthesis), computer vision (CV), reinforced learning (RL) and related methods.
You will be part of a close-knit team of applied scientists and product managers 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 with 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 cutting edge research to raise the bar within the team.

As a Generative AI Audio-Video Applied Scientist on this team, you will:
- Drive end-to-end Machine Learning projects that have a high degree of ambiguity, scale and complexity.
- Build 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.
- Perform hands-on analysis and modeling of enormous data sets to develop insights that 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.
- Research new and innovative machine learning approaches.
- 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 generative audio (e.g. musicalisation, ambient audio, synthetic speech) and the related foundational models to augment generative imagery and videos. You will develop core models that will be the foundational of the core advertising-facing tools that we are launching. You will conduct literature reviews to stay on the cutting edge of the field. You will regularly engage with product managers, who will partner with you to productize your work.

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 growing team of applied scientists 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:

USA (Seattle, CA), UK (London, Bristol, Edinburgh)

We are open to hiring candidates to work out of one of the following locations:

Seattle, WA, USA


- 2+ 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


- Advanced degree in Computer Science, Mathematics, Statistics, Economics, or related quantitative field.
- Published relevant research work in academic conferences or industry circles.
- Experience in building large-scale machine-learning models and infra for online recommendation, ads ranking, personalization, or search, etc.
- Effective verbal and written communication skills with non-technical and technical audiences.
- Experience working with large real-world data sets and building 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.
- Experience in computational advertising.

Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit

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 $222,200/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 Applicants should apply via our internal or external career site.