Description

The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through generative AI technologies, revolutionizing how millions of customers discover products and engage with brands across Amazon.com and beyond. We are at the forefront of re-inventing advertising experiences, bridging human creativity with artificial intelligence to transform every aspect of the advertising lifecycle from ad creation and optimization to performance analysis and customer insights. We are a passionate group of innovators dedicated to developing responsible and intelligent AI technologies that balance the needs of advertisers, enhance the shopping experience, and strengthen the marketplace. If you're energized by solving complex challenges and pushing the boundaries of what's possible with AI, join us in shaping the future of advertising.

Sponsored Products Search Relevance’s (SPSR) team’s mission is to help shoppers easily find and discover the most useful and relevant sponsored products, while improving advertisers’ ability to find the right shoppers in the right context for their sponsored products. We develop capabilities to understand shoppers’ queries, shopping missions, and products’ attributes so that we can identify ASINs that are contextually relevant to the shopper. We make CX/UX improvements so that shoppers can easily perceive why products are relevant to them and efficiently navigate Amazon’s vast product selection.

As an MLE on the team, you will collaborate with scientists, product managers, work backwards from customers, identify the problems, propose innovative solutions, mentor junior engineers, raise the bar, and have a positive impact on hundreds of millions of customers.

Key job responsibilities section

* Design and build scalable services to support advertising infrastructure
* Collaborate with scientists and engineers to design and build data pipelines for processing massive datasets and scaling ML and LLMs.
* Productionize LLM/VLM models, with a focus on efficiency, throughput, and low-latency serving.
* Provide architectural guidance and technical leadership to ensure solutions deliver measurable improvements in customer perceived relevance.
* Quickly learn technologies and algorithms in the field of Generative AI.