Faire is looking to improve the quality of its product listings using machine learning and AI techniques.
Requirements
- 5+ years of industry experience using machine learning to solve real-world problems
- Experience with relevant technical methods (e.g. LLM fine tuning, deep learning, or human-in-the-loop machine learning)
- Strong programming skills
- Experience with supervised fine tuning of multi-modal LLMs
- Experience with listing quality for e-commerce
Responsibilities
- 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.
- Mentor and guide the work of more junior Data Scientists on Listing Quality.
- Act as a lead on the cross-functional Listing Quality pod, thinking end-to-end about brand and retailer experiences, ops processes, policy enforcement, etc.
Other
- Master’s or PhD in Computer Science, Statistics, or related STEM fields
- Strong communication skills and the ability to work in a highly cross-functional team
- The ability to mentor Senior Data Scientists, develop team strategy, and lead model development without supervision
- In-office on a hybrid schedule - Faire employees will be expected to go into the office 2 days per week on Tuesdays and Thursdays
- Flexibility to work remotely up to 4 weeks per year
