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?
Join Back Market's AI Core team as we accelerate AI adoption across the company and turn conversations into action. Our team built Back Market's first ML and AI applications and continues to advance AI capabilities. We've presented our LLM research at several applied AI conferences, showcasing for instance how we blend large language models with traditional ML techniques. This innovative approach gives us deeper insights into customer interactions, which translates into a meaningfully improved platform experience for our users.
As an AI Core Data Science and AI Intern, you will focus on understanding and evaluating Large Language Models (LLMs) in one of two key settings, depending on business priorities and your interests. You will build and run evaluation frameworks, compare models, uncover blind spots and failure modes, and partner with engineers and product teams to translate findings into improvements. The first setting involves LLMs used as feature extractors in internal tools, where we combine LLM-derived signals with machine learning models to produce actionable KPIs and predictions. The second setting focuses on LLM-based chatbots, an area we're actively exploring, where you'll develop rigorous evaluation and red teaming approaches to ensure reliability, safety, and the best consumer experience.
This internship is central to our AI strategy, highly visible, and offers a rare opportunity to have transformative impact. You will contribute to production systems used across the business while learning fast in a hands-on environment.
Develop and implement comprehensive LLM evaluation frameworks to assess performance and reliability across two key applications:
LLM evaluation in our tech stack: Evaluate the accuracy and consistency of LLMs integrated within our technology and analysis stack, for instance to extract meaningful insights from customer conversations (sentiment, tone, behaviors) or other technical applications. You'll uncover potential blind spots, analyze failures, and compare different models and parameters to identify which perform best for our specific use cases and how to generalize this approach.
Chatbot Applications: Design thorough testing methodologies to explore edge cases, conduct red teaming exercises, and ensure reliable performance across diverse user interactions and scenarios. You'll also evaluate implementation considerations including optimal model choice and model parameters, prompt engineering strategies to ensure both safety and customer experience.
Collaborate closely with engineering and product teams to translate evaluation insights into actionable improvements, helping guide model selection decisions and system enhancements
Support the team's broader ML initiatives by contributing to statistical analysis, data science projects, and other machine learning efforts that align with your skills, interests, and the team's evolving priorities
Mandatory: Currently enrolled in your last year of an Engineering School with specialization in Data Science/Engineering or University Master's degree and your university can provide an internship agreement
Strong foundation in AI/ML concepts; experience working with Large Language Models is appreciated
Proficiency in Python and experience with ML libraries
Analytical mindset with experience in data analysis and statistical evaluation methods
Passionate about AI innovation and eager to work with cutting-edge technologies
Strong problem-solving skills with attention to detail in model evaluation and testing
Our working language is English; fluency is required (no French required)
Bonus Points:
Experience with LLM frameworks (OpenAI API, etc.)
Knowledge of AI evaluation metrics and benchmarking methodologies
Familiarity with conversational AI and chatbot technologies
Starting date: March 2026
Duration: 6 months (until September 2026)
Schedule: Full-time (35H/week)
Location: Paris, France
Contract: Internship agreement from your French school required
Video-call Interview with the Campus Tech Recruitment Manager (30min)
Video-call Technical fit interview : Live coding + open talk (45min) with the tutor
Video-call Team fit interview with 2 engineers/members from the team (30min)
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.
Rencontrez Paul, VP of Engineering
Rencontrez Dawn, CTO
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