Senior Applied AI/ML Scientist - Search
About The Position
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 this role As a Senior Applied AI/ML Scientist on the Search group, you’ll help shape the technical vision, machine-learning algorithm strategy, and system design behind one of our most important growth levers: Search (think about what you do when you land on any e-commerce site). You’ll advance real-time Search and Recommendation systems that power next-generation shopping experiences. You’ll work at the frontier 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 every user query. This is a rare chance to influence end-to-end personalization in a high-scale, deeply multi-modal environment while collaborating closely with a talented team of scientists and engineers.
Requirements
- 4+ years of experience building large-scale ML systems, including 2+ years in search, recommendation, or ads ranking.
- Hands-on experience with deep-learning libraries (e.g. PyTorch) and vector-search infrastructure (e.g. Faiss, ScaNN, Pinecone).
- A strong record of productionizing models that blend LLMs (e.g. BERT, GPT-class) with structured features to drive personalization.
- A product-focused mindset and a bias toward execution—you move quickly from paper to prototype to production.
- Strong Python skills, deep respect for system reliability and ownership, and experience operating in high-stakes environments.
- Excellent communication and cross-functional influence that raise the technical bar beyond your immediate team.
Nice To Haves
- Contributions to open-source ML libraries or peer-reviewed publications in ML/AI.
- Master’s or PhD in Computer Science, Statistics, or a related STEM field.
Responsibilities
- Contribute to our next-generation Search engine by integrating LLMs, query understanding, dense-vector retrieval, deep personalization embeddings, multi-stage ranking, and reinforcement learning to serve personalized product feeds with sub-100 ms latency.
- Design and productionize natural-language search and discovery systems so that intelligent agents can generate relevant and personalized collections, explain search results, and assist retailers with browsing, filtering, and evaluation.
- Lead model development and GPU-based deployment efforts, leveraging frameworks like Triton to scale inference reliably and efficiently.
- Share best practices around model development, agent-workflow evaluation, and MLOps, and help teammates level up through code reviews and technical guidance.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Number of Employees
1,001-5,000 employees
