Overview In this role you own end-to-end ML projects that uphold marketplace trust by matching Faire's catalog to external data, detecting pricing and policy violations, and prioritizing remediation within a constrained budget. You'll apply multimodal models and feature engineering across structured and unstructured data to power detection and enrichment, partnering with product, engineering, and operations. You'll shape experiments and measurement to drive impact on retailer trust and GMV. This role places you at the core of Faire's mission to empower local businesses through data-driven safeguards.
Compensation / Benefits- equity and benefits
- competitive pay
- career growth opportunities
- hybrid work options
- focus on inclusion/belonging
- life-work balance initiatives
Responsibilities- Own applied ML projects end-to-end from framing to production and impact measurement
- Develop pricing-integrity models comparing listings to external signals and detecting pricing violations with calibrated confidence
- Solve product matching and entity resolution at scale using text/image embeddings, retrieval, and multimodal LLMs
- Extract structured attributes from unstructured content to power detection and enrichment
- Translate model scores into actionable prioritization under a constrained human-review budget
- Build human-in-the-loop systems with operations partners: audits, training labels, precision bars
- Design experiments for enforcement levers (downranking, badging, remediation) and measure impact on trust and GMV
- Collaborate with product, engineering, operations, and analytics to ship models as product features
- Address challenges of a two-sided marketplace
Key requirements- 3+ years of industry ML experience solving real-world problems
- Experience with e-commerce, marketplaces, catalog/content quality, search, or personalization
- Experience with DL/LLMs, computer vision, information extraction, entity resolution, ranking, and/or experimentation and causal inference
- Strong programming skills
- Willingness to learn new tools and techniques
- Ability to drive a project end-to-end with limited supervision
- Strong communication skills and cross-functional collaboration abilities
- cross-functional collaboration
- clear communication
- problem framing and ownership
- deep learning and LLMs
- computer vision
- information extraction
