Data Engineer

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

Skills

• 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
• Tech Stack

Experience with: Python, Databricks, AWS, Kafka, Airflow, Prefect, MLflow, TensorFlow, Triton, PyTorch, vLLM, KServe, Delta Lake, Kubernetes, SQL, Terraform, Apache Spark

• Languages
• French: Fluent (C2 level required)
• English: Fluent (B2/C1 level required)
• 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.

Want to learn more about how we build our AI infrastructure? Read our latest article: Open source at the core, proprietary where it counts: Mirakl's AI inference platform — by Jeanine Harb, Antoine Bourgault and Maxime Roodnejad, Senior Data Engineers at Mirakl.

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.

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.

• 🗓️ 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

• 💡 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

Data Engineer

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.

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.

About Mirakl

Mirakl is the leading provider of eCommerce software solutions. Mirakl's suite of solutions provides enterprises with a transformative way to drive significant growth and efficiency in their online business.

Since 2012, Mirakl has been pioneering the platform economy, empowering retail and B2B enterprises with the most advanced, secure, and scalable technology to digitize and expand product assortment through marketplace and dropship, improve efficiency in supplier catalog management and payments, personalize shopping experiences, and boost profits through retail media.

In July 2025, Mirakl launched Mirakl Nexus, the first neutral infrastructure designed for agentic commerce. Built on Mirakl's 13 years of expertise and innovation, and powered by an ecosystem of more than 100,000 sellers, Mirakl Nexus connects merchants and AI agents to automate product discovery, payments, and after-sales service.

For more information: www.mirakl.com.

This is a permanent position (CDI) based in Paris, with 4 days on-site per week.

• 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.

• Your Impact
• Design and implement a performant, robust, and scalable ML Platform architecture — covering training, evaluation, and inference — while keeping costs under control