About the job
About Faire
Faire is a dynamic online wholesale marketplace dedicated to empowering local businesses. We believe in a future where independent retailers can thrive and compete against retail giants like Walmart and Amazon. By harnessing technology, data, and machine learning, we connect a vibrant community of entrepreneurs globally. Imagine helping your favorite local boutique source outstanding products from around the world to enhance their offerings. Our mission is to provide the tools and insights that enable small businesses to succeed in a competitive landscape.
By championing the growth of independent businesses, Faire fosters positive economic impacts within communities worldwide. We are on the lookout for intelligent, resourceful, and passionate individuals to join our team as we drive the shop local movement. If you share our commitment to community, we invite you to be part of ours.
About this role
At Faire, we leverage advanced machine learning and data insights to transform the wholesale industry, enabling local retailers to stand strong against larger competitors. The Data Science team is pivotal in developing and sustaining a variety of algorithms and models that enhance our marketplace. We focus on creating innovative machine learning models that empower our customers to succeed.
As a member of the Brand Data Science team focused on Listing Quality, your role will involve enhancing the quality of product listings, enabling retailers to effectively discover and assess products on Faire. You will apply ML and AI to address key challenges, including improving image and text quality, extracting structured product attributes, and accurately identifying duplicates and product variants. Utilizing deep learning, multi-modal LLMs, and a human-in-the-loop approach, you'll deliver high-performance solutions. In this rapidly evolving domain, you will be at the forefront of applying cutting-edge technology to drive tangible outcomes. You will independently design and implement solutions while collaborating with the cross-functional Listing Quality pod, which includes product, design, engineering, analytics, and operations, to tackle challenges comprehensively.

