Data Engineer at Mirakllabs
- Company: Mirakllabs
- Location: Paris
- Employment type: full-time
- Posted: 2026-11-13
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
1. The Team You'll Join
You'll be part of our Data Experience squad led by Alexandre Blanchard , Data Engineering Manager within Mirakl's broader Data team of 70 specialists. Together, you'll be building and scaling the ML infrastructure that powers Mirakl's AI-driven products from real-time recommendation inference to LLM fine-tuning pipelines serving some of the world's most innovative e-commerce players.2. Your Impact
- Design and implement a performant, robust, and scalable ML Platform architecture — covering training, evaluation, and inference — while keeping costs under control
- Maintain and improve ML production pipelines and real-time inference applications at scale (real-time recommendation inference, 1M+ LLM calls/week, async content moderation)
- Partner with Data Scientists from project kickoff through productionization — setting up best practices, guardrails, and CI/CD improvements in collaboration with the SRE team
- Drive technical excellence: manage technical debt, systematize version upgrade processes, and upskill team members on MLOps and Data Engineering topics
- Contribute to cutting-edge AI projects — including LoRA adapter creation for open-source LLM fine-tuning, in-house computer vision models, and large-scale product data transformation — and share findings across Labs teams
3. What You'll Bring to the Role
Experience:- 2+ years of experience in a Machine Learning and/or Data engineering environment
- Proven track record of shipping ML applications at scale (NLP, image processing, or classical ML) in high-volume, production-grade systems
- Background in software development with a strong appetite for data science and machine learning
- Proficiency in Python and the Kubernetes/Docker ecosystem
- Solid experience with cloud environments (AWS primarily) and Apache ecosystem frameworks
- Hands-on knowledge of an orchestration tool (Airflow, Prefect, or equivalent)
- Familiarity with CI/CD practices and MLOps principles (monitoring, model lifecycle, reproducibility)
- Strong communicator with a knack for mentoring and presenting technical work to diverse audiences
4. Tech Stack
Experience with: Python, Databricks, AWS, Kafka, Airflow, Prefect, MLflow, TensorFlow, Triton, PyTorch, vLLM, KServe, Delta Lake, Kubernetes, SQL, Terraform, Apache Spark5. Languages
- French: Fluent (C2 level required)
- English: Fluent (B2/C1 level required)
6. Our Hiring Process
We warmly encourage you to apply to any of our roles, even if you think you're not an exact match. Please click the "Apply" button to submit your application — this helps us make the best possible assessment and get back to you as quickly as possible.- A 30-40 min phone conversation with one of our Tech recruiters. This will be an opportunity to discuss your background, expectations, and discover what Mirakl can offer you in return.
- An initial 1 hour technical discussion with a member of the Data Science team and Engineering Team, which will allow you to delve into the more specific aspects of your expertise and discover how your skills can be integrated into our projects.
- 1 hour discussion with your futur manager
- 2 x 45-minute "STAR" interviews with future Mirakl colleagues to discuss our values and company culture.
We welcome collaborators with their diverse perspectives and experiences to power us forward. These often far exceed conventional job requirements and help us create a culture of continuous learning. If you’re ready to join a global leader powering digital transformation for 450+ of the world’s most innovative retailers and B2B organizations.
As part of our recruitment process, Mirakl processes your personal data to review and manage your application and, where appropriate, to consider your profile for future opportunities. You can exercise your data protection rights at any time, and as further detailed in our policies. For more information about how we process your personal data and your rights, please consult our Recruitment Privacy Notice, here in English and here in French.
We may use Artificial Intelligence (AI) solutions to help streamline our hiring process, including screening applications, analyzing resumes, and assessing responses. While AI helps us work efficiently, all final hiring decisions are made by humans. For more information, visit our AI Guidelines for Candidates and Interviews .
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