AI Content & Knowledge Manager Intern

Posted 6 Days Ago
Be an Early Applicant
Paris, Île-de-France, FRA
In-Office
Internship
eCommerce • Greentech • Sharing Economy
Our startup revolutionizes the way people buy tech devices
The Role
Evaluate and improve Fin, Back Market’s AI customer care agent, by reviewing conversations, monitoring quality scorecards, identifying defects and root causes, analyzing performance across markets and use cases, and tracking corrective actions. The intern will document evaluation frameworks and provide actionable feedback to product, engineering, content, and data teams.
Summary Generated by Built In
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 clearly in English.

  • You are curious, detail-oriented, pragmatic, and comfortable investigating ambiguous problems.

  • You can distinguish facts, hypotheses, and open questions.

BONUS POINT : Experience with LLM evaluation, prompt evaluation, conversational AI, or human-in-the-loop systems is a plus. French is helpful but not required.

ABOUT THE INTERNSHIP:
  • Start date: January 2027

  • Duration : 6 months

  • Full-time internship (35h/week)

  • Location : Paris (France)

RECRUITMENT PROCESS: 📅
  • Skill fit interview and live case study with a team member (45min)

  • Video-call Interview with the Talent Acquisition Specialist (30 min)

  • Cultural fit interview with the manager (30min)

WHY SHOULD YOU JOIN US ? ✌🏼

At Back Market, we’re committed to hiring and supporting diverse teams of people from all backgrounds, experiences, and perspectives — it’s one of the reasons we’re such a high-scoring certified B Corp company (93.2).

No matter your role and seniority level, you’ll enjoy impact-driven work with hands-on career development in an innovative, driven, and fast-paced environment — with benefits to match, like:

- A mission driven work environment where your day to day makes an impact on the planet. Seriously.

- Hybrid work environment, with 2 remote days a week and 1 remote work week per quarter, plus 3 flex days.

- Employee Resource Groups, including mentorship programs, comprehensive accessibility policies, and cultural competency training.

At Back Market, we strive to create a workplace that embodies the world we’re trying to change. We’ve embedded our diversity, equity, and inclusion principles into our DNA — from dedicated staff to employee resource groups to our company values.

We know that the perfect background for a role doesn’t mean the perfect fit — we encourage you to apply for a role even if you think you may not have all the qualifications.

If reasonable accommodations are needed for the interview process, please do not hesitate to discuss this with the Talent Acquisition Team.

Skills Required

  • Currently completing a Master 2 degree in Data Science, Applied Mathematics, Statistics, or another engineering discipline
  • Strong analytical and problem-solving skills
  • Comfort working with data and investigating anomalies
  • Interest in generative AI, machine learning, or LLM evaluation
  • Ability to structure and communicate findings clearly in English
  • Curious, detail-oriented, pragmatic, and comfortable investigating ambiguous problems
  • Ability to distinguish facts, hypotheses, and open questions
  • Experience with LLM evaluation, prompt evaluation, conversational AI, or human-in-the-loop systems
  • French language skills
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The Company
HQ: Paris
450 Employees
Year Founded: 2014

What We Do

At the heart of Back Market is a simple idea: make devices a bit cleaner by making them last a bit longer. We think it's time to offer a strong and mainstream alternative to new products by making existing used devices more appealing to potential customers and making them accessible as a strong alternate option.

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