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Senior Applied Ai Ml Scientist Listing Quality

Applied AI Scientist (Hybrid)💼 Full-time💰 $180,000–$180,000🗓 2026-07-25

Core

Improving the quality of product listings on Faire's marketplace by enhancing image and text quality, extracting structured attributes, and identifying duplicates/variants using ML and AI.

Role type

Senior Applied AI/ML Scientist (Listing Quality)

Builds

High-performance ML solutions for e-commerce product data quality

Domain

E-commerce / Wholesale marketplace

Deliverable

production ML models

Required skills

Deep learning, LLM fine-tuning, human-in-the-loop training, multi-modal LLMs, structured data extraction, duplicate detection, variant identification, end-to-end solution design

Preferred skills

Supervised fine-tuning of multi-modal LLMs, deploying and optimizing LLM inference systems at scale (10B+ tokens), cost efficiency optimization

Technologies

LLMs, deep learning frameworks, multi-modal models

Responsibilities

Drive data science vision and strategy for Listing Quality; automatically detect and address listing issues with high accuracy; lead cross-functional pod on brand and retailer experiences

Seniority

Senior, hands-on IC with lead responsibilities

Rewrite
## About the role Faire leverages the power of machine learning and data insights to revolutionize the wholesale industry, enabling local retailers to compete against giants like Amazon and big box stores. At Faire, the Data Science team is responsible for creating and maintaining a diverse range of algorithms and models that power our marketplace. We are dedicated to building machine learning models that help our customers thrive. As a member of the Brand Data Science team working on Listing Quality, you will be responsible for improving the quality of product listings to help retailers find and evaluate products on Faire. You will use ML and AI to tackle critical challenges, such as enhancing image and text quality, extracting structured product attributes, and accurately identifying duplicates and product variants. You will leverage deep learning, multi-modal LLMs, and human-in-the-loop training to create high performance solutions. This space has been evolving rapidly with advancements in AI and you will be at the forefront of applying the latest technology to drive real-world impact. You will independently design and implement solutions and work with the cross-functional Listing Quality pod, including product, design, engineering, analytics, and operations, to solve problems end-to-end. ## What you'll do - Drive data science vision, strategy, and execution on Listing Quality, using ML and AI solutions to improve the quality of Faire's product listings. - Use deep learning, LLM fine tuning, and human-in-the-loop training to automatically detect and address issues with high accuracy. - Act as a lead on the cross-functional Listing Quality pod, thinking end-to-end about brand and retailer experiences. ## Qualifications - 3+ years of industry experience using machine learning to solve real-world problems - Experience with relevant business problems (e.g. e-commerce) - Experience with relevant technical methods (e.g. LLM fine tuning, deep learning, or human-in-the-loop machine learning) - Strong programming skills - An excitement and willingness to learn new tools and techniques - The ability to design and implement ML solutions without supervision - Strong communication skills and the ability to work in a highly cross-functional team ## Great to Haves - Master's or PhD in Computer Science, Statistics, or related STEM fields is highly recommended - Previous experience in listing quality for e-commerce - Previous experience in supervised fine tuning of multi-modal LLMs - Experience deploying and optimizing LLM inference systems at scale (10B+ tokens), with focus on cost efficiency and product impact ## About the company Faire leverages the power of machine learning and data insights to revolutionize the wholesale industry, enabling local retailers to compete against giants like Amazon and big box stores. At Faire, the Data Science team is responsible for creating and maintaining a diverse range of algorithms and models that power our marketplace. We are dedicated to building machine learning models that help our customers thrive.
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