About the position
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. Our highly skilled team of data scientists and machine learning engineers specialize in developing algorithmic solutions for notification and recommender systems, advertising attribution, and LTV predictions. Our ultimate goal is to empower local retail businesses with the tools they need to succeed. 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 the Listing Quality lead within the Brand Data Science team, you will be responsible for improving the quality of Faire's product listings using ML and AI techniques. This includes problems such as automatically detecting and fixing image and text issues, extracting structured product attributes, and identifying duplicates and product variants. You will leverage deep learning, multi-modal LLMs, and human-in-the-loop training to create high performance solutions. You will mentor and guide the work of more junior Data Scientists who also work on Listing Quality. You will independently drive data science vision, strategy, and execution and be the data science lead within the cross-functional Listing Quality pod, thinking end-to-end about the problem. Our team already includes experienced Data Scientists from Uber, Airbnb, Square, Facebook, and Pinterest. Faire will soon be known as a top destination for data scientists and machine learning engineers, and you will help take us there!
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.
Requirements
- 5+ years of industry experience using machine learning to solve real-world problems.
- Experience with relevant business problems.
- 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 mentor Senior Data Scientists, develop team strategy, and lead model development without supervision.
- Strong communication skills and the ability to work in a highly cross-functional team.
Nice-to-haves
- Master's or PhD in Computer Science, Statistics, or related STEM fields.
- Previous experience in listing quality for e-commerce.
- Previous experience in supervised fine tuning of multi-modal LLMs.
Benefits
- Equity and benefits eligibility.
- Flexible remote work up to 4 weeks per year.
