Staff Applied ML/AI Scientist - Search

About Faire Faire is a technology wholesale platform built on the belief that the future is local. Independent retailers around the globe collectively represent a multi-hundred-billion-dollar wholesale market that has historically been fragmented and offline. 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 businesses can grow and local communities can thrive. 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 a Staff Applied AI/ML Scientist on the Search Group, you’ll drive the technical vision, ML algorithm strategy, and system design powering one of the most critical levers for customer value and company growth—Search (think about what you do when you land on any e-commerce site). You’ll lead 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/brands for any given query from the users. This is a rare opportunity to own end-to-end personalization in a high-scale, deeply multi-modal environment—while mentoring a team of talented scientists and engineers. What You’ll Do Own 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 <100ms latency. Design and productionize natural language search and discovery systems, enabling intelligent agents to generate relevant and personalized collections, explain search results, and assist retailers in browsing, filtering, and evaluation. Lead model development and GPU-based deployment efforts, leveraging frameworks like Triton to scale inference reliably and efficiently. Mentor and grow senior Applied Scientists and MLEs, and establish best practices around model development, agent workflow evaluation, and MLOps. You’re a Great Fit If You Have… 7+ years of experience building large-scale ML systems, including 3+ 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 track 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—you raise the technical bar beyond your immediate team. Bonus Points For… Contributions to open-source ML libraries or peer-reviewed publications in ML/AI. MS or PhD in Computer Science, Statistics, or a related STEM field. Strong practices around model development, agent workflow evaluation, and MLOps. Salary Range US: the pay range for this role is $231,000 to $318,000 per year. This role will also be eligible for equity and benefits. Actual base pay will be determined based on permissible factors such as transferable skills, work experience, market demands, and primary work location. The base pay range provided is subject to change and may be modified in the future. Hybrid Faire employees currently go into the office 3 days per week on Tuesdays, Thursdays, and a third flex day of their choosing (Monday, Wednesday, or Friday). Additionally, hybrid in-office roles will have the flexibility to work remotely up to 4 weeks per year. Specific Workplace and Information Technology positions may require onsite attendance 5 days per week as will be indicated in the job posting. Why you’ll love working at Faire Move fast: You'll own meaningful problems that serve customers around the globe with the agency to move fast and see your results clearly. Equipped to scale: We invest in what matters, including the latest enterprise AI tools, to help you work smarter and get more out of every day. Best in class: Our team is full of sharp, kind, and generous colleagues who care about their craft and about helping you grow in yours. Real rewards. Competitive pay, equity, and comprehensive benefits designed to support your life inside and outside of work. Belonging: We're intentional about building an environment where every Faire employee has equal access to opportunities, growth, and success. Faire was founded in 2017 by a team of early product and engineering leads from Square. We’re backed by some of the top investors in retail and tech including: Y Combinator, Lightspeed Venture Partners, Forerunner Ventures, Khosla Ventures, Sequoia Capital, Founders Fund, and DST Global. We have headquarters in San Francisco and Kitchener-Waterloo, and a global employee presence across offices in Toronto, London, and New York. To learn more about Faire and our customers, you can read more on our blog. Faire provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, genetics, sexual orientation, gender identity or gender expression. Faire is committed to providing access, equal opportunity and reasonable accommodation for individuals with disabilities in employment, its services, programs, and activities. Accommodations are available throughout the recruitment process and applicants with a disability may request to be accommodated throughout the recruitment process. We will work with all applicants to accommodate their individual accessibility needs. To request reasonable accommodation, please fill out our Accommodation Request Form ( Privacy For information about the type of personal data Faire collects from applicants, as well as your choices regarding the data collected about you, please visit Faire’s Privacy Notice (