Senior Machine Learning Engineer for AI Product
Qonto
Job Overview
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Job Description
About Qonto
Our mission is to create the freedom for SMEs to succeed in business and beyond by delivering Europe’s leading finance workspace. We combine business-class tools such as seamless invoicing, spend management, and pre-accounting with unwaveringly attentive 24/7 support, designed to help businesses breeze through all things finance.
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.
Discover the steps we took to create a discrimination-free hiring process.
Join us as a Senior 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. 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! 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 as an 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.
We are looking for someone who can be based in one of our offices (Paris or Barcelona), as this position is not open to fully remote arrangements.
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 I L'Usine Digitale | Courrier Cadres
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Key skills/competency
- Machine Learning Engineering
- Generative AI
- MLOps
- Python
- Client-facing Product Development
- Model Deployment
- Scalable Solutions
- Data Pipelines
- Monitoring & Alerting
- Problem Solving
How to Get Hired at Qonto
- Research Qonto's culture: Study their mission, values, recent news, and employee testimonials on LinkedIn and Glassdoor.
- Tailor your resume: Highlight ML engineering expertise, client-facing product development, and Python proficiency.
- Showcase project impact: Quantify measurable results from past ML model deployments and MLOps initiatives.
- Prepare for technical deep dives: Brush up on Generative AI, Python, scalable systems, and cloud-based ML infrastructure.
- Emphasize problem-solving: Be ready to discuss complex ML challenges and your proactive solutions effectively.
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