Senior Machine Learning Engineer For Ai Product

OverviewDescrizione dell’offerta di lavoroOur mission? Creating the freedom for SMEs to succeed in business and beyond, by delivering Europe’s leading finance workspace. We combine business-class tools (seamless invoicing, spend management, and pre-accounting) with attentive 24/7 support, designed to help businesses breeze through all things finance.Our journey: Founded by Alexandre and Steve in July 2017, Qonto has rapidly gained trust, serving over 600,000 customers. Thanks to our team of 1,600+ Qontoers, we also made it to the LinkedIn Top Companies French rankingOur values: Customer focus | Ownership | Teamwork | Mastery | IntegrityIntegrity: Always do what’s right, and respect people.Our beliefs: At Qonto, we’re committed to fostering a welcoming environment where everyone can thrive. We prioritize evaluating applicants based solely on skills and potential, ensuring diversity with 55% international team members, 44% women, and 20% parents. Join us in building a workplace that celebrates diversity and individuality.Discover the steps we took to create a discrimination‑free hiring process.Role: Machine Learning Engineer, AI ProductJoin us as a Machine Learning Engineer for our AI Product team to build and ship customer‑facing AI for 500,000+ business customers, combining Generative AI with proven machine‑learning techniques. You’ve delivered client‑facing products end‑to‑end and can show measurable impact (adoption, faster task completion, satisfaction) while ensuring reliability, privacy, and continuous monitoring in production. You must have developed client‑facing products.You will work closely with Marianne Ducournau and join a team of 8 AI Engineers and 3 Data Ops, creating innovative solutions that are at the core of Qonto\'s financial services.Senior Machine Learning Engineer, AI Product: you will develop new models end‑to‑end, align with Product Managers, Data Engineers, and Backend Engineers to ensure seamless integration of ML solutions into the product ecosystem.Develop models: design, train, evaluate, and iterate on ML models using modern techniques tailored to real business problems.Put models into production: robust technical implementation and quality assurance processes.Scale our solutions: create an ML Ops framework with monitoring and alerts (model drift detection, performance tracking, automated retraining pipelines).Share best practices within the ML team, contribute to internal knowledge, tooling, and mentoring peers.What you can expectMarket / Team ContextMethodologies and tools: Python, Cursor, Snowflake, Kafka, Kibana, PostgreSQL, Airflow, AWS tools, Prometheus, ArgoCD, GitHub. Freedom to test tools as long as they help reach the target.Growth opportunities: clear individual contributor track to become an expert and work on the latest AI.Your Future Manager: Marianne, Head of Data ProductsMarianne has managed Data Science teams in Finance and joined Qonto 3 years ago to build our Data Science team. She mentors and coaches the team.About YouExperience: 3+ years of experience as ML Engineer with ML Ops, developing client‑facing products. Familiar with tools that automate model retraining and performance checking.Modeling expertise: experience building and optimizing ML models for external clients.Software Engineering: proficient in Python, writing resilient, high‑quality, testable code, and integrating with third‑party services and databases at scale and FastAPI or a similar web framework.Problem‑solving: track record of solving complex problems in ML contexts.Proactivity: take initiative to improve processes.Language: English proficiency.We are looking for someone who can be based in Paris or Barcelona; this role is not fully remote.At Qonto we understand that true diversity isn’t just about ticking boxes on a hiring checklist. Apply regardless of the boxes you tickPerksOffices in Paris, Berlin, Milan, Barcelona, and Belgrade;Competitive salary package;Meal vouchers;Public transportation reimbursement (partial or global);Health insurance (depending on country);Employee well‑being initiatives: access to Moka Care for mental health and wellness offers;Disability and parenthood policy with selected partners;Monthly team events.Our hiring process: Interviews with Talent Acquisition Manager and future managers; remote or live skill exercise; information on interview process on careers site; process lasts about 20 working days with offers usually within 48 hours.To learn more about us: Qonto\'s Blog | Les Échos | L\'Usine Digitale | Courrier Cadres.To know how your personal data will be processed during your application, please click here.Creare un avviso di lavoro per questa ricerca#J-18808-Ljbffr