About Faire
Faire is an online wholesale marketplace built on the belief that the future is local — independent retailers around the globe are doing more revenue than Walmart and Amazon combined, but individually, they are small compared to these massive entities. At Faire, we're using the power of tech, data, and machine learning to connect this thriving community of entrepreneurs across the globe. Picture your favorite boutique in town — we help them discover the best products from around the world to sell in their stores. With the right tools and insights, we believe that we can level the playing field so that small businesses everywhere can compete with these big box and e-commerce giants.
By supporting the growth of independent businesses, Faire is driving positive economic impact in local communities, globally. We’re looking for smart, resourceful and passionate people to join us as we power the shop local movement. If you believe in community, come join ours.
About the Role
As an Applied AI/ML Scientist on the Search Group, you’ll work with world-class machine learning scientists to execute the ML algorithm strategy and system design powering one of the most critical levers for customer value and company growth—Search. You’ll collaborate on the advancement of real-time Search and Recommendation systems behind our next-generation shopping experiences.
You’ll operate at the forefront of algorithms—combining large language models, natural-language processing, query understanding, deep learning, transformer-based sequential modeling, graph neural networks, and structured behavioral data to return hyper-relevant, personalized products and brands for any given query.
This is a rare opportunity to work on end-to-end Search/Recommendation in a high-scale, deeply multi-modal environment, where we bring together the top talents from companies including Google, Meta, Amazon, LinkedIn, Uber, Airbnb, Salesforce, Twitter, Square, Pinterest, Instacart, and Coupang.
What You’ll Do
Contribute to the next-generation Search engine, integrating LLMs, query understanding, dense vector retrieval, deep personalization embeddings, multi-stage ranking, and reinforcement learning to serve personalized product feeds with
