Staff Applied AI/ML Scientist
$247k - $339k • Remote • San Francisco, CA
Posted 1mo ago
Job Location
San Francisco, CA
Tech Stack
Remote Work Policy
Fully remote
Categories
Applied AI Engineer
About the job
Faire leverages machine learning and data insights to revolutionize the wholesale industry, empowering local retailers to compete against larger players. Our Applied AI/ML Scientists develop algorithmic solutions for recommender systems, spend optimization, and lifetime value predictions. As a tech lead in this role, you will own the vision, strategy, and execution for a set of problems that power Faire's two-sided marketplace, connecting hundreds of thousands of independent brands and retailers. You will work across structured and unstructured data using various ML methods and act as a lead across multiple cross-functional workstreams, mentoring other scientists.
Responsibilities
- Drive data science vision, strategy, and execution end-to-end, and act as a pod lead across cross-functional workstreams.
- Develop personalized recommendation, retrieval, and ranking models, and build content and retailer-level embeddings.
- Optimize marketing, acquisition, and incentive spend through targeting and personalization, and measure effectiveness using experimentation and causal inference.
- Predict lifetime value to prioritize sales and acquisition efforts and personalize the new-user experience.
- Improve cold-start recommendations and exploration for new users and new selection.
- Extract insights from internal and external data to enrich leads and power personalization.
- Use deep learning, multi-modal LLMs, and human-in-the-loop training to understand listings and content, extract structured attributes, and detect issues.
- Build detection, enforcement, and quality systems to reduce bad experiences in the marketplace.
- Re-engage users through personalized marketing and identify gaps and opportunities that drive increased engagement.
- Mentor or manage Senior Applied AI/ML Scientists and Analytics Engineers.
- Solve challenging problems related to a two-sided marketplace.
Requirements
- 5+ years of industry experience using machine learning to solve real-world problems.
- Experience with relevant business problems (e-commerce, marketplaces, growth, personalization, incentives, or trust and quality).
- Experience with relevant technical methods (causal inference, predictive/LTV modeling, recommendations, information extraction, entity resolution, deep learning, and/or LLMs).
- Strong programming skills.
- Willingness to learn new tools and techniques.
- Experience as a tech lead, mentoring other scientists or machine learning engineers, and the ability to set team strategy and lead model development without supervision.
- Strong communication skills and ability to work in a highly cross-functional team.
- Master's or PhD in Computer Science, Statistics, or related STEM fields (highly recommended).
- Previous experience in marketplace growth, incentive optimization, or trust and quality for a two-sided platform (preferred).
- Previous experience with deep learning or language models (preferred).
Benefits
- Equity
- Benefits