Senior Applied AI/ML Scientist - Listing Quality
$211k - $291k • San Francisco, CA
Posted 22d ago
Job Location
San Francisco, CA
Tech Stack
Remote Work Policy
On-site
Categories
Applied AI Engineer
About the job
Faire is seeking a Senior Applied AI/ML Scientist to join the Listing Quality team. This role will focus on developing and implementing algorithmic solutions to revolutionize the wholesale industry by improving product catalog content. You will be responsible for the modeling and measurement of product images, titles, descriptions, and attributes, leveraging multi-modal deep learning and LLMs to enhance product discoverability and sales. This is a high-impact position where you will drive projects end-to-end, from problem framing to production and measurement, working with unstructured data to solve challenging marketplace problems.
Responsibilities
- Own applied ML projects end-to-end, including problem framing, model building, shipping, and impact measurement.
- Utilize multi-modal deep learning and LLMs to analyze listing content, extract structured product attributes, and identify quality issues at scale.
- Enhance product imagery through selection, ordering, cropping, and enhancement techniques.
- Develop ranking and exploration strategies to optimize content performance for different audiences.
- Improve listing text (titles, descriptions, information coverage) and measure its impact on discovery and conversion.
- Build and validate LLM-as-judge and human-in-the-loop evaluation systems, ensuring they meet accuracy standards before influencing production decisions.
- Collaborate with product, engineering, design, and analytics teams to integrate models into products and drive business impact.
- Address complex challenges within a two-sided marketplace.
Requirements
- 3+ years of industry experience applying machine learning to solve real-world problems.
- Experience with relevant business areas such as e-commerce, marketplaces, catalog/content quality, search, or personalization.
- Proficiency in technical methods including deep learning, LLMs, computer vision, information extraction, entity resolution, ranking, and/or experimentation/causal inference.
- Strong programming skills.
- Eagerness to learn new tools and techniques.
- Ability to lead projects end-to-end with limited supervision.
- Strong communication skills and ability to work effectively in cross-functional teams.
Benefits
- Equity
- Health insurance
- Paid time off
- Hybrid work arrangement with flexibility to work remotely up to 4 weeks per year.