Senior Machine Learning Engineer

Our mission? Making day-to-day banking easier for SMEs and freelancers thanks to an online business account that's combined with invoicing, bookkeeping and spend management tools. Thanks to its innovative product, highly reactive 24/7 customer support and clear pricing, Qonto has become the leader in its market.
Our journey: Founded by Alexandre and Steve in July 2017, Qonto has rapidly gained trust, serving over 500,000 customers. Thanks to our wonderful team of 1,600+ Qontoers, we also made it to the LinkedIn Top Companies French ranking!
Our values:Customer focus | Prioritize customers in everything you doOwnership | Own your part, get things doneTeamwork | Make (team)work easyMastery | Continuously raise the barIntegrity | 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 50% 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.
Are you a talented Machine Learning Engineer ready to make a significant impact? Qonto invites you to join our dynamic Fraud Security team, working alongside three experienced ML Engineers to create, deploy, and train powerful machine learning models.
⭐ Your mission? Elevate our fraud detection capabilities and ensure the security of Qonto's clients' assets by staying ahead of sophisticated fraudsters.
👩‍💻🧑‍💻 As a Machine Learning Engineer at Qonto, you will:
- Develop and implement risk assessment models, including enhancing our recently launched model for evaluating organizational scam risk.- Apply your expertise in Python, SQL, and ML libraries to enhance predictive modeling and feature engineering.- Contribute to the entire development cycle, from modeling and development to production deployment, infrastructure management, and incident handling.- Collaborate on projects ranging from simple expert rules to advanced machine learning and generative AI applications.- Strengthen the team's machine learning capabilities, complementing existing data product skills.- Mentor junior team members and contribute to the team's growth and knowledge sharing.- Engage in full-stack data engineering to craft robust ETL processes and maintain clean, structured data tables.- Take full ownership of the ML infrastructure, utilizing tools like Kubernetes and AWS for efficient model deployment.- Continuously improve existing models, balancing the creation of new solutions with the optimization of our current systems
🤝 About your future Manager: You will work closely with Jérémy, our Lead Machine Learning Engineer
What about him:
Jérémy leads the risk scoring and anti-fraud team with a pragmatic, results-oriented, and caring management style. He empowers team members to take ownership of their projects while providing support through weekly one-on-one meetings and open communication. Jérémy believes in fostering growth, encouraging skill development, and maintaining a trust-based environment where feedback is valued and micromanagement is avoided.
🤔 What you can expect:
Team Context: Join an autonomous, cutting-edge team combating financial fraud.Work Environment: Experience a fast-paced, asynchronous, and decisive setting, emphasizing analysis and engineering excellence.Tools in Action: Utilize top-notch infrastructure—Kubernetes, AWS, PostgreSQL, Snowflake, and Kafka—for efficient development.Building Everything: Play a crucial role in shaping a startup-like ecosystem within our scaleup, contributing from the ground up.Ownership: Master the entire process, own the roadmap, and foster openness to innovative ideas.Impactful Role: Make a strong, visible impact, reporting directly to the Leadership team, shaping the future of our mission.
🏅 About You
Mindset: You naturally explore the data before building any model, you are proficient in feature engineering techniques to extract meaningful insights from complex datasets.User-focused and outcome-oriented: You want to solve high-impact business problems and deliver value to our users in productionMastery: You are proficient with Python, Pandas, CatBoost, and Scikit-learn. You care about the craft and champion high standards.Outcome-oriented: You value simplicity and think impact first.Software Engineering best practices: you document, version, and test your code systematically.Communication: You appreciate the teamwork that data products typically require, and you have effective communication skills, to build alignment and articulate purpose.Language: You are fluent in English.
🌏 Location: You can choose to work in a full-remote mode as long as you're living in (or willing to relocate to) either Germany, France, Italy, Serbia or Spain.
At Qonto we understand that true diversity isn't just about ticking boxes on a hiring checklist. Apply regardless of the boxes you tick! Who knows? You may have the missing piece of the puzzle we've been searching for all along.🎁 Perks
A tailor-made and dynamic career track. An inclusive work environment. And so much more to help you succeed.
- Offices in Paris, Berlin, Milan, Barcelona, and Belgrade;- Tailor-made remote work policy depending on the job you apply for and where you live;- Competitive salary package;- A meal voucher;- Public transportation reimbursement (part or global);- A great health insurance (depending on the country);- Employee well-being initiatives: access to Moka Care to take care of your mental health and great offers for sports and wellness activities;- A progressive disability and parenthood policy (1 in 6 of Qonto employees is a parent!) and childcare benefits with selected partners;- Monthly team events.
💪 Our hiring process:
- Interviews with your Talent Acquisition Manager and future managers- A remote exercise to demonstrate your skills and give you a taste of what working at Qonto could be like
We will send you an interview guide so you can best prepare yourself.On average, our process lasts 20 working days and offers usually follow within 48 hours 🤞

To learn more about us:Qonto's Blog | Les Échos I L'Usine Digitale | Courrier Cadres

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