Senior ML Engineer - Fraud

Our 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 unwaveringly 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 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 do
• Ownership | Own your part, get things done
• Teamwork | Make (team)work easy
• Mastery | Continuously raise the bar
• Integrity | 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.

Discrimination‑free hiring process

Discover the steps we took to create a discrimination‑free hiring process.

Machine Learning Engineer – Fraud Security team

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 experienced ML Engineers to create, deploy, and train powerful machine learning models.

Your mission

⭐ Your mission? Elevate our fraud detection capabilities and ensure the security of Qonto’s clients' assets by staying ahead of sophisticated fraudsters.

Responsibilities

• 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 scale‑up, 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.

With Qonto’s rising profile attracting increasingly sophisticated threats, every day brings new challenges to solve.

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 production.

Mastery: 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.
• Competitive salary package.
• Meal vouchers.
• 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 or live exercise to demonstrate your skills and give you a taste of what working at Qonto could be like.

Find more information about our interview process on our careers website.

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 | L'Usine Digitale | Courrier Cadres

To know how your personal data will be processed during your application process or to request its deletion, please click here.

#J-18808-Ljbffr