Machine learning engineer (f/m/d)

Overview

At IDnow, we believe innovation is finding solutions to problems that don’t yet exist but are sure to impact our future. Making the connected world a safer place is and has been our vision from the very beginning.

Our identity verification SaaS solutions enable businesses to make reliable, informed decisions in an instant. We offer robust, secure and seamless solutions to protect against player fraud, identity theft or forging signatures. It is not only mandatory and reduces business loss, but it also becomes a highly competitive advantage, as customer experience and retention rates improve substantially. We help our clients to increase security, improve customer conversion, and streamline their onboarding process.

We understand that regulation and our clients’ requirements are constantly evolving, so we evolve with them. Thanks to our close relationships with industry regulators, our solutions comply with multi-jurisdictional KYC ("Know Your Customer") regulations, allowing customers to process a wide variety of identity documents, and onboard and service consumers from all around the world in different markets and countries.

This position is based in Rennes, France.

IDnow, Europe’s leader in identity verification solutions (KYC, eSigning, IDcheck, etc.), is strengthening its RDM (Research Data Management) division. We are looking for a Machine Learning Engineer passionate about data and industrialization to design and operate the tools and data storage that power our software and AI research.


Key Responsibilities

* Design, implement, and manage data storage and data management solutions for our software.
* Develop tools and frameworks enabling AI & ML R&D teams to train our algorithms and allowing engineering teams to run product test campaigns.
* Manage and analyze large data volumes.
* Set up and maintain backend APIs and services that provide reliable and secure internal data access.
* Contribute to the industrialization of data/ML workflows (CI/CD, containerization, deployments) with a strong focus on quality (automated testing).
* Collaborate closely with internal stakeholders (ML teams, product design and development, QA) in an agile environment to prioritize and deliver within a continuous improvement process.


Preferred Experience

Technical Skills:

* API frameworks and REST APIs (FastAPI/Django REST or equivalent).
* Automated testing with pytest; strong quality and coverage mindset.
* SQL databases: strong “wide database culture,” mastery of PostgreSQL and MariaDB (modeling, performance, query optimization, migrations).
* Data storage: design and operation of data storage solutions (a major plus).
* Docker: containerization and best practices; basic orchestration appreciated.
* Multidisciplinary teams (AI/ML research, development, QA), agile methodology.
* Internal clients, strong impact on quality and innovation speed.
* Demanding yet supportive environment.
* At the heart of identity verification challenges.
* DevOps: CI/CD setup (GitLab CI), deployment automation (Ansible).
* Linux: day-to-day administration and tooling (shell, security, permissions, networking).

What You’ll Bring

* The ability to translate R&D needs into robust, scalable, and well-tested data platforms and tools.
* Technical leadership on data lifecycle management (ingestion, storage, access, traceability) in service of AI and testing.
* An industrialization mindset (automation, reproducibility, observability) applied to ML and data workflows.

Soft Skills

* Motivation and initiative.
* Curiosity, appetite for technical challenges, and continuous learning.
* Team spirit, clear communication with diverse stakeholders (engineers, researchers, QA).
* Rigor, service orientation, and product mindset.
* English required (international environment).
* Health & Wellbeing: access to mental health resources and 1on1 sessions.
* Personal and professional development: training platforms with 24/7 access and certifications.
* Remote work support, flexible working hours.
* Onsite gatherings, internal initiatives and social events.
* Paid special leave days for personal or family needs.
* Workcation opportunities to combine work with travel.
* Specific benefits that differ between locations.

IDnow applies the principles of non-discrimination and equality. We strive to maintain 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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