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Senior Machine Learning Engineer for AI Product

Roles & Responsibilities

  • 3+ years of experience as a ML Engineer with ML Ops, including development of client-facing products.
  • Strong modeling expertise: building, training, evaluating, 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; experience with FastAPI or a similar web framework.
  • Proactive problem-solving and fluent English communication.

Requirements:

  • Develop new models end-to-end—from understanding product requirements to implementation and deployment—aligning with Product Managers, Data Engineers, and Backend Engineers to ensure seamless integration into the product ecosystem.
  • Design, train, evaluate, and iterate ML models using modern techniques tailored to real business problems; put models into production with robust implementation and quality assurance processes.
  • Scale solutions by creating an ML Ops framework to ensure models scale effectively with monitoring and alerts (e.g., drift detection, automated retraining pipelines) and by sharing best practices within the ML team.
  • Mentor peers and contribute to internal tooling and knowledge sharing to uplift the team's ML capabilities.

Job description

Our mission and customers
 
Our platform simplifies banking and finance management for SMEs today, so that they can build their tomorrow. We offer a finance management platform with banking at its core, augmented by financial tools. We are proud to be rated 4.8 on Trustpilot, based on 53,000+ reviews.
 
Our culture puts customer satisfaction at the core of what we do, as proven by our Net Promoter Score of 75. This level of satisfaction is far above typical traditional banking scores, often ranging from 3 to 12, sometimes even lower.
 
Our journey 
 
Founded in 2017 by Alexandre and Steve, Qonto has grown to 1,600+ Qontoers serving over 600,000 customers across 8 European countries: France, Germany, Italy, Spain, Portugal, Austria, Belgium, and the Netherlands. We have been profitable since 2023, and we are just getting started as we want to become the indisputable European leader in SME finance management.
 
Our beliefs
 
We hire for skills and potential. With 80+ nationalities, 45% women, and 56% of women in our leadership team, diversity is simply part of who we are. 
 
We've built a discrimination-free hiring process because we believe the best teams are built on merit.
 
AI at Qonto
 
We see AI as a catalyst for our success.
We always choose thinking over routine. That's why AI is already deeply embedded in how we work - not as a trend, but as a way to raise the bar for the entrepreneurs who count on us. That is why we grant our Qontoers unlimited access to the best AI tools on the market - Claude Code, Cursor, Copilot, Dust, and Notion AI.
We want people who experiment without waiting for permission. Who push AI beyond the obvious. Who know when to trust it and, more importantly, when to question it. 
 
Already pushing AI limits? You'll fit right in.
 
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Join 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.

👩‍💻🧑‍💻 As a Senior Machine Learning Engineer for our AI Product team at Qonto, you will:

• Develop new models end-to-end, from understanding product requirements to implementation and deployment:
- Align with various stakeholders, including 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 with robust technical implementation and quality assurance processes
• Scale our solutions:
- Create an ML Ops framework for the team to ensure our models scale effectively with proper monitoring and alerts (e.g., model drift detection, performance tracking, automated retraining pipelines)
- Share best practices within the ML team, contributing to internal knowledge, tooling improvements, and mentoring peers

🤔 What you can expect:

• Market/Team Context: Your work will have visible and direct impact on Qonto's users and experience.
• Methodologies and tools: We use a modern tech stack including Python, Cursor, Snowflake, Kafka, Kibana, PostgreSQL, Airflow, AWS tools, Prometheus, ArgoCD, and GitHub. You'll have the freedom to test any tool as long as it helps reach the target.
• Growth opportunities: There's a clear individual contributor track for those who want to become experts in their field and the opportunity to work on the latest AI

🤝 Your Future Manager

Your Future Manager will be Marianne, Head of Data Products.

Her background?
After her experience in famous tech organizations where she managed Data Science teams in the Finance department, Marianne joined Qonto 3 years ago to build our Data Science team!

What does she bring to the team?
As an expert in her field, she has hands-on experience in implementing Data Science models to serve cross-functional teams and deliver actionable insights. Marianne also has a true passion for mentoring and coaching the team.

🏅About You:

• Experience: You have 3+ years of experience ML Engineer coupled with ML Ops, particularly in developing client-facing products. You're familiar with tools that automate model retraining and performance checking.
• Modeling expertise: You have experience building and optimizing machine learning models for external clients.
• Software Engineering: You're proficient at writing resilient, high-quality, testable code in Python, and you understand how to integrate with third-party services and databases at scale and FastAPI or a similar web framework.
• Problem-solving: You have a proven track record of identifying complex problems and implementing effective solutions in machine learning contexts.
• Proactivity: You take the initiative to improve processes and don't wait for problems to arise before addressing them.
• Language: You are fluent in English.

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.
Our hiring process
 
- Interviews with your Talent Acquisition Manager and future managers (1 hour each)
- A remote or live exercise to demonstrate your skills and give you a taste of what working at Qonto could be like
 
On average, our process lasts 20 working days - more information here on our candidate journey.
 
To know how your personal data will be processed during your application process or to request its deletion, please click here.

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