🧡 ABOUT ALMA At Alma, we believe sustainable commerce depends on fair, well-balanced trade. Because finance plays a pivotal role in business, our mission is to put it back in its rightful place - serving merchants and consumers. Our installment and deferred payment solutions help merchants boost sales by 20% or more, increase customer loyalty, and deliver a seamless shopping experience - without encouraging bad debt. As the buy now pay later leader in France and active in 10 European countries, we've empowered over +25,000 merchants and 10 million consumers. With 380+ Almakers and €100M+ ARR, Alma is scaling rapidly across Europe as a member of the Next40, and we're just getting started!   👐 ABOUT THE TEAM The AI team is part of the Data department. We build and operate the ML products at the core of Alma's business such as credit-scoring to offer a frictionless payment experience while minimizing defaults and maximizing acceptance. We've recently broadened our scope beyond risk into AI for operational intelligence - delivering AI solutions that make Alma's operational teams more effective and answer new business needs, including revenue forecast and debt collection optimization. So you'll work across both our core risk models and a growing portfolio of new ML initiatives. We're a team of five, owning our products end-to-end, from modelling all the way to the production systems that serve and monitor them. You'll report to the ML Engineering Manager (Bastien) and work closely with Data, SRE and Quantitative Analysis. This is a full-time position, based in Paris or fully remote in France.   💼 ABOUT THE JOB As a Machine Learning Engineer, you'll own ML products end-to-end - splitting time between developing models, and the platform that runs them. Concretely, you will: * Own ML models across their full lifecycle - from data pipelines and feature engineering to training, evaluation, deployment and monitoring; choosing the right metrics and guarding against leakage, overfitting and drift. * Run and improve our ML platform - own the team's GitOps CI/CD and release process, monitor serving endpoints, latency and load in Datadog, and define the SLOs and alerting that keep models reliable in production. * Turn ML into business value across the org - collaborate with risk, operational and product teams to spot and ship ML opportunities, from credit scoring to AI for operational intelligence, sharing your expertise through code reviews and tech watch.   🧰 YOU WILL WORK WITH Python, scikit-learn, SQL, Vertex AI Pipelines (Kubeflow), dbt, BigQuery, PostgreSQL, Argo Workflows, Neo4j, FastAPI, Argo CD, Kubernetes, Terraform, Datadog   🧩 ABOUT YOU To succeed in this job * You have 5+ years building and shipping ML in production: strong Python and SQL, solid ML fundamentals (evaluation, leakage, over/under-fitting), and clean, tested, reviewable code. We expect you to be familiar with some elements of our stack. * You're hybrid - hands-on with MLOps and infrastructure (data pipelines, monitoring, system design, live prediction / streaming) and at ease reasoning about latency, scale and reliability. * You're autonomous, analytical and business-driven, with professional English and working proficiency in French (the team's day-to-day language). And it will be nice if you also * Have experience with GCP, Docker, or graph databases. * You have experience with LLMs, both as development tools and as components embedded in product systems. * Have a background in credit scoring, BNPL ("Buy Now Pay Later"), or financial services and fraud. Don't meet every single requirement? At Alma, we believe great hires come from diverse paths. If this role excites you, we encourage you to apply. We value potential, curiosity and the ability to grow as much as experience.   🧘 WHAT'S IN IT FOR YOU If you join, you will be able to grow and impact on: * Visible impact - your models directly move Alma's bottom line, and you'll see it in the scoring and debt collection KPIs. * A modern ML platform to build on and improve - a GitOps/MLOps stack (Argo CD, GitHub Actions, dbt, Datadog) you'll own and shape. * Real breadth - from core risk models to AI for operational intelligence, with genuine ownership across modelling and infrastructure in a small, autonomous team.   🤑 COMPENSATION & BENEFITS * Competitive salary based on 12 months * Profit-sharing and employee savings plan * Health insurance: 100% covered by Alma including family package * Disability insurance: 100% covered by Alma * Sport: partnerships with Gymlib and Classpass, or €30/month reimbursement for your sports activities * Maternity/paternity leave: salary maintained at 100% during leave with no seniority requirement. Return to work at 4/5 schedule paid at 100% for 8 weeks. * Sustainable Mobility Package (FMD): €544.80/year (excluding full-remote contracts) * Meal vouchers: €10/day, 50% covered by Alma * Mental health: free access to MindDay platform * Paid time off: 25 days/year (+ additional paid leave granted for employees on executive contracts) * Access to our Learning & Development Platform * 2 weeks of full remote possible per year in summer for people working in hybrid remote   🎯 INTERVIEW PROCESS * Video call with a Talent Acquisition team member to understand your path, motivation & present you the role. * Video call with your future manager to deep-dive a significant project you've owned, the team and the role. * Applied ML, coding and ML system design discussion with 2–3 team members - a live, hands-on build to assess your craft, modelling judgment. * Fit interview with a senior leader to assess values, motivation and ways of working.   🌍 DIVERSITY & INCLUSION At Alma, we believe that diversity fuels innovation and makes our community stronger. We are committed to building a workplace where every person feels seen, respected, and empowered to do their best work whatever their gender, background, ethnicity, age, sexual orientation, religion, disability or lived experience. As an equal opportunity employer, we welcome applicants from all walks of life, and all employment decisions are made based on qualifications, merit, and business needs.