Senior Data Scientist NLP/GenAI - Catalog
Mirakl - Labs
| Company | Mirakl - Labs |
| Category | Data & Analytics |
| Location | Bordeaux |
| Remote | On-site (inferred) |
| Employment | Not stated |
| Level | Senior |
| Salary | Not stated by the employer |
| Posted | 25 Oct 2024 |
| Last verified | 8 Aug 2026 |
| Source | Employer ATS (greenhouse) |
Description
About Mirakl:
Founded in 2012, Mirakl has been at the forefront of marketplace innovation, empowering every business to compete in the platform economy. Today, Mirakl’s operating system combines an enterprise marketplace solution (Mirakl Platform) that enables retailers and B2B organizations to launch, scale, and operate marketplaces and dropship, AI-powered multichannel selling (Mirakl Connect), retail media (Mirakl Ads) and an agentic commerce infrastructure (Mirakl Nexus). With dual headquarters in Boston and Paris, Mirakl helps a global ecosystem of 450+ marketplaces (B2C and B2B) and a network of over 100k third-party marketplace sellers. Brands like Macy’s, Decathlon, Carrefour, Asos, and Airbus Helicopters use Mirakl to grow their businesses in new and remarkable ways.
For more information: www.mirakl.com .
Mirakl in Numbers:
🗓️ Founded in 2012 | Member of French Tech Next40
👥 750+ employees in 9 offices worldwide: Paris, Barcelona, Bordeaux, Boston, London, Munich, New York, Sydney, Tokyo
🇫🇷 350+ Mirakl Tech teams members mainly based in France
⚙️ 5 Saas Solutions
Our Values:
Working at Mirakl means accelerating your career alongside ambitious, passionate, and supportive colleagues. We're proud of the diversity of backgrounds, perspectives, and experiences that make our teams unique.
Our 5 values guide how we collaborate:
💡 Work Hard Together: Teamwork and collaboration are the foundation of our success
🏆 Get Things Done: We prioritize action and efficiency for impactful results
🚀 Go Above & Beyond: We tackle challenges proactively and always aim for excellence
🎓 Succeed Through Expertise: Knowledge sharing and continuous learning are core to our culture
🤝 Satisfy & Empower Clients: We're committed to our clients' success
The Team You'll Join
You'll be part of our Catalog Data Science team led by Arthur Delaitre and Adrien Morvan .
As part of our broader Data team (60+ people), you'll be prototyping, iterating, and shipping algorithms to production that directly impact marketplace catalog challenges—from NLP to large-scale Generative AI with custom LLMs.
Our opportunity can be located in Paris or Bordeaux and requires 4 days onsite per week, 1 day remote.
Meet Arthur Delaitre , Data Science Manager for the team:
Your Impact
Build and deploy ML algorithms to production that power 500+ e-commerce and marketplace sites across 40 countries, directly impacting revenue growth, operational efficiency, and transaction safety
Tackle real-world catalog challenges including automatic content rewriting, product attribute extraction from images and text, variant detection, product categorization, seller onboarding automation, and trending product prediction
Work with cutting-edge AI techniques including multimodal models and LLM fine-tuning—Mirakl is one of the few French players with fine-tuned LLMs in large-scale production
Own your projects end-to-end : from data analysis and prototyping to production deployment with Data Engineers and dev teams, plus building dashboards to monitor algorithm performance
Collaborate across teams to refine use cases, user experience, and integration paths while presenting results at weekly data science meetings
What You'll Bring to the Role
Experience:
6+ years of experience as a Data Scientist with strong hands-on NLP and applied ML in industry
Proven track record of deploying Machine Learning algorithms to production
Experience with Spark development for large-scale data processing
Skills:
Expertise in NLP and Computer Vision algorithms and state-of-the-art architectures (e.g., Transformers)
Proficiency in Python and TensorFlow and/or PyTorch
Knowledge of the latest LLMs and fine-tuning techniques
Data-driven, pragmatic, and business-oriented approach
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