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Salary: USD 211,000 - 290,500 / annual
Faire is a technology wholesale platform connecting independent retailers globally with suppliers. As a Senior Applied AI/ML Scientist on the Search team, you will shape the technical vision and machine-learning strategy behind Faire's search and recommendation systems—a critical growth lever for the platform.
You will advance real-time search and recommendation systems that power next-generation shopping experiences by combining 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.
Key responsibilities include:
- Building next-generation search ranking algorithms by integrating the latest advances in deep learning and machine learning to personalize the retailer discovery journey
- Leveraging LLMs to extract multimodal signals (text, visual) to better profile users and their intents
- Partnering closely with cross-functional teams to experiment and improve ML models for search ranking and beyond
- Designing and productionizing 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
- Sharing best practices regarding deep learning model development, agent-workflow evaluation, and MLOps; helping teammates level up through code reviews and technical guidance
This is a rare opportunity to influence the end-to-end personalized discovery experience at Faire within a high-scale, deeply multi-modal environment while collaborating with a talented team of scientists and engineers.
Workplace: Hybrid (3 days per week in office on Tuesdays, Thursdays, and a flex day; up to 4 weeks remote per year).
REQUIREMENTS:
- 5+ years of industry experience building large-scale ML models with business impact and shipping ML solutions to production, including 3+ years in search, recommendation, or ads ranking
- Master's or PhD in Computer Science, Statistics, or a related STEM field
- Strong programming skills (Python, Java, or equivalent) and hands-on experience with deep-learning libraries (e.g., PyTorch) and big data technologies (e.g., Spark)
- Deep understanding of machine learning best practices (training/serving, imbalanced data, A/B testing, feature engineering, feature/model selection) and algorithms (user modeling, deep learning, reinforcement learning) with applications in search, recommendation, and advertising domains
- Product-focused mindset and bias toward execution—moving quickly from research papers to prototypes and production
- Excellent written and verbal communication skills and strong cross-functional influence that raises the technical bar beyond your immediate team
BONUS:
- Contributions to open-source ML libraries or peer-reviewed publications in ML/AI
- Industry experience developing and productizing LLM-based applications and systems in the search domain
- Industry experience building search and recommendation systems for e-commerce or two-sided marketplaces
- Experience using AI tools (e.g., Cursor, Claude Code, Codex) for code development and daily productivity
- Familiarity with Kotlin
