Faire is looking to solve the problem of empowering local retail businesses to compete against giants like Amazon and big box stores through the use of machine learning and data insights.
Requirements
- 4+ years of industry experience using machine learning to solve real-world problems
- Experience and strong understanding of personalization for product development
- Strong Machine Learning / Deep Learning modeling and programming skills
- Ability to quickly implement state-of-the-art algorithms from an academic paper
- Previous experience with graph neural network and/or language models
- Strong understanding of retrieval embeddings models, near-real-time / streaming signals, Deep Learning or LLM based ranking / recommendation models, explore-exploit, and diversification
Responsibilities
- Personalizing recommendation across surfaces of homepage, category page, brand page and carousel recommendations
- Developing algorithmic solutions related to discovery, ranking, search, recommendations, ads, logistics, underwriting, and more
- Working on cutting-edge personalization and recommendation problems by combining a wide variety of data about retailers, brands, and products
- Solving challenging problems related to a two-sided marketplace
- Implementing state-of-the-art algorithms from academic papers
- Quickly implementing new tools and techniques
Other
- Strong communication skills and the ability to work with others in a closely collaborative team environment
- Master’s or PhD in Computer Science, Statistics, or related STEM fields (highly recommended)
- Ability to work in-office on a hybrid schedule (2 days per week)
- Ability to work remotely up to 4 weeks per year
- 4+ years of industry experience
