Sr Applied Scientist, CreativeX

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 time aims to democratize access to high-quality creatives (text, audio, images, videos) 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 have a proven record of developing Generative AI science at the highest standards of innovation, and experience working and delivering product-ready code, are adept at a variety of skills, especially with LLMs, generative 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 innovation research to raise the bar within the team. - 6+ years of building machine learning models or developing algorithms for business application experience
- PhD, or Master's degree and 6+ years of applied research experience
- Experience with large scale machine learning systems such as profiling and debugging and understanding of system performance and scalability
- Experience with neural deep learning methods and machine learning
- Knowledge of programming languages such as C/C++, Python, Java or Perl