Applied AI/ML Scientist - Search

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 the Role

As an Applied AI/ML Scientist on the Search Group, you’ll work with world-class machine learning scientists to execute the ML algorithm strategy and system design powering one of the most critical levers for customer value and company growth—Search. You’ll collaborate on 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 and brands for any given query. 

This is a rare opportunity to work on end-to-end Search/Recommendation in a high-scale, deeply multi-modal environment, where we bring together the top talents from companies including Google, Meta, Amazon, LinkedIn, Uber, Airbnb, Salesforce, Twitter, Square, Pinterest, Instacart, and Coupang.

What You’ll Do

• Contribute to 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 <100 ms 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.
• Collaborate on model development and GPU-based deployment efforts, leveraging frameworks like Triton to scale inference reliably and efficiently.

You’re a Great Fit If You Have…

• 1-3 years of industry or research experience using machine learning to solve real-world problems, ideally including work in search, recommendations, 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.

Salary Range

California & New York: the pay range for this role is $162,500 to $223,500 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.

Effective January 2025, Faire employees will be expected to go into the office 2 days per week on Tuesdays and Thursdays. 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. 

Applications for this position will be accepted for a minimum of 30 days from the posting date.

Why you’ll love working a