AI Content & Knowledge Manager Intern

Job description

Hi, we’re Back Market. We’re here to help make tech reliable, affordable, and better than new . We're a global marketplace for refurbished devices, helping lower our collective environmental impact by providing trustworthy, affordable tech with 92% less carbon emissions than new. Yep, you read that right. Turns out refurbished tech is way better for the planet than new. In fact, With every device purchased on Back Market, our positive impact on the planet grows. From our Customer Care representatives to our software engineer, every individual at Back Market cuts the planet — and consumers — a break. Our mission is simple: to do more with what we already have. Are you ready to join us? JOB DESCRIPTION: Back Market is building AI-powered customer care experiences through Fin, its customer-facing AI Agent. Fin helps customers with pre-sales questions, delivery tracking, and technical troubleshooting. As an AI Quality & Evaluation Intern, you will work with the QA Lead to monitor Fin’s performance, review conversations, identify recurring issues, and help improve the quality evaluation process. You will collaborate with content, product, data, and engineering teams to turn your findings into concrete improvements. YOUR MISSION (IF YOU ACCEPT IT): 🥇 Operate and improve quality monitors and scorecards covering accuracy, policy compliance, connector use, escalation quality, tone, hallucinations, and unsupported claims. Review flagged and unflagged conversations to identify false positives, false negatives, and recurring defects. Prepare the weekly quality review by summarizing key findings, risks, and root causes. Analyse Fin’s performance across markets, languages, use cases, and rollout phases. Monitor handovers to human agents and customer satisfaction signals. Track corrective actions, owners, and validation status. Improve the documentation and versioning of Fin’s evaluation framework. Share clear, actionable feedback with product, engineering, content, and data teams. YOU ARE IN THE RIGHT PLACE IF: ⭐ You are completing a Master 2 degree in Data Science, Applied Mathematics, Statistics, or another engineering discipline. You have strong analytical and problem-solving skills. You are comfortable working with data and investigating anomalies. You are interested in generative AI, machine learning, or LLM evaluation. You can structure and communicate findings cl…