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IDnow is a leader in digital identity and fraud prevention in Europe with a mission to transform trust into the most powerful asset in the digital world, empowering enterprises with AI-driven, SaaS-based identity solutions that deliver scalable security, adaptive compliance, and real-time fraud prevention. Through its broad portfolio of digital identity and fraud prevention solutions, IDnow establishes, maintains and enriches trust throughout the customer journey, ensuring businesses can confidently and securely operate while leveraging digital identity to drive growth, security and scalability.
The company has offices in Germany, United Kingdom, Romania and France, and is backed by renowned institutional investors, including Corsair Capital and Seventure Partners. Its portfolio of international clients spans a wide range of end markets including financial services, telecommunications, travel & mobility, gaming, and other industries.
This position is based in Rennes, France.
As an experienced Python Developer, you will join our AI & ML team responsible for developing and integrating AI‑based fraud detection algorithms into our micro‑services infrastructure. Your objective will be to design such services and bring our algorithms from the prototyping stage to production for continuous improvement of our fraud detection and prevention capabilities.
You are an expert in Python with strong skills in building complex services, ideally related to fraud detection. You master graph database architecture. You have basic knowledge of Machine Learning and Artificial Intelligence. Curious, rigorous, and impact‑oriented, you know how to transform raw, complex algorithms into reliable and operational services within a critical architecture.
Nice to have:
IDnow applies the principles of non-discrimination and equality: We strive to establish, maintain, and promote an open and inclusive recruitment process and working environment by respecting the principles of equal opportunities. Including but not limited to: sex, race or ethnic origin, religion or convictions, gender identity, citizenship, marital status, disability, age, or sexual orientation.
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