Faire

Senior Applied AI/ML Scientist - Search Ranking

Faire • $211K — $290K *
Consumer Technology
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • 5+ years of industry experience in building large-scale ML models with business impact
  • 3+ years specifically in search, recommendation, or ads ranking
  • Master's or PhD in Computer Science, Statistics, or a related STEM field
  • Strong programming skills in Python, Java or equivalent, with experience in deep-learning libraries like PyTorch
  • Deep understanding of machine learning best practices and algorithms applicable in search and recommendations
  • Product-focused mindset with a bias toward rapid execution

Responsibilities

  • Build next-gen Search ranking algorithms using deep learning and machine learning
  • Leverage LLM to extract multimodal signals for user profiling
  • Collaborate closely with cross-functional teams to experiment with ML models
  • Design natural-language search systems for personalized collections and results
  • Share best practices surrounding deep learning model development and MLOps

Benefits

  • Opportunity to own meaningful projects that impact global customers
  • Access to the latest enterprise AI tools to enhance productivity
  • A collaborative and growth-oriented team environment
  • Competitive pay, equity, and comprehensive benefits
  • Commitment to building an inclusive workplace with equal opportunities
Full Job Description
About the role

As a Senior Applied AI/ML Scientist on the Search team, you will help shape the technical vision, machine-learning algorithm strategy, and system design behind one of our most important growth levers: Search (the primary tool used by customers on any e-commerce site). You will advance real-time search and recommendation systems that power next-generation shopping experiences.

You'll work at the frontier of algorithms, 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.

This is a rare chance to influence the end-to-end personalized discovery experience at Faire within a high-scale, deeply multi-modal environment, while collaborating closely with a talented team of scientists and engineers.

What you'll do
  • Build our next-generation Search ranking algorithms by integrating the latest advances in deep learning and machine learning to personalize the retailer discovery journey at Faire
  • Leverage LLM to extract multimodal signals (text, visual) to better profile users and their intents.
  • Partner closely with teams across Faire to experiment and improve the ML models for search ranking and beyond.
  • 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.
  • Share best practices regarding deep learning model development, agent-workflow evaluation, and MLOps, and help teammates level up through code reviews and technical guidance.

You're a great fit if you have...
  • 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
  • A 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 (e.g., training/serving, imbalanced data, A/B testing, feature engineering, and feature/model selection) and algorithms (e.g., user modeling, deep learning, and reinforcement learning) with applications in search, recommendation, and advertising domains.
  • A product-focused mindset and a bias toward execution-moving quickly from research papers to prototypes and production.
  • Excellent written and verbal communication skills and strong cross-functional influence that raise the technical bar beyond your immediate team.

Bonus points for...
  • 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

Salary Range

San Francisco: the pay range for this role is $211,000 to $290,500 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.

About Faire

Faire is an online wholesale marketplace that connects independent retailers with small and medium-sized brands. The company offers a range of products such as home decor, jewelry, and accessories. Faire was founded in 2017 and is headquartered in San Francisco, California. The company has over 600 employees and operates in the United States, Canada, and Europe. Faire has raised over $400 million in funding and has partnerships with over 150,000 retailers and 15,000 brands.
Learn more about Faire
Size
600 employees
Industry
Founded
2017

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