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Salary: USD 211,000 - 290,500 / annual
Faire is a technology wholesale platform connecting independent retailers globally with suppliers and products. As a Senior Applied ML/AI Scientist on the Search team, you will shape the technical vision and machine-learning strategy behind Faire's search and recommendation systems—a core growth lever for the platform.
You'll work on next-generation search ranking algorithms that combine query understanding, deep learning, transformer-based sequential modeling, graph neural networks, and behavioral data to deliver hyper-relevant, personalized product and brand recommendations. The role spans the full ML lifecycle: algorithm design, LLM integration for multimodal signal extraction (text, visual), model productionization, and agent-workflow systems that help retailers discover, filter, and evaluate products.
Key responsibilities include building search ranking algorithms using latest deep learning advances; leveraging LLMs to extract multimodal signals for user profiling and intent understanding; partnering across teams to experiment and improve ML models; designing and productionizing natural-language search systems with intelligent agents; and sharing best practices on deep learning development, evaluation, and MLOps while mentoring teammates through code reviews and technical guidance.
You bring 5+ years of industry experience building large-scale ML models with business impact and shipping production solutions, including 3+ years in search, recommendation, or ads ranking. You hold a Master's or PhD in Computer Science, Statistics, or related STEM field. You have strong programming skills (Python, Java, or equivalent), hands-on experience with deep-learning libraries (PyTorch) and big data technologies (Spark), and deep understanding of ML best practices and algorithms. You're product-focused, bias toward execution, and excel at cross-functional communication and influence.
Bonus qualifications include open-source ML contributions or peer-reviewed publications; experience developing and productionizing LLM-based applications in search; e-commerce or two-sided marketplace search/recommendation experience; familiarity with AI coding tools; and Kotlin knowledge.
Hybrid role: 3 days per week in office (Tuesdays, Thursdays, plus one flex day), with flexibility to work remotely up to 4 weeks annually.
