Machine learning Engineer

Being a Machine Learning Engineer at Floryn means you see yourself as a blend of statistician, data scientist, researcher, and engineer. At Floryn, predictive models are playing a crucial role in predicting financial health of our clients and it is expanding rapidly to other credit-risk areas. Your expertise will directly contribute to our mission of pioneering innovative credit-risk solutions.

As part of our Data Science team, you’ll be working on our regression models, data pipelines, deployment, validation, feature engineering processes, etc. In a scale-up like Floryn a diverse skill set is invaluable. The goal is to make the best possible predictions to improve the credit-risk process (PD, LGD, Labelling). Our hierarchy is flat and communication is direct, therefore we can operate and adapt quickly. All our stakeholders are internal and mainly come from the Risk and Development team.

About Floryn

Floryn is one of the fastest growing fintech companies in the Netherlands. We aim to be the most responsible, scalable and customer-friendly online lender in Europe. We’ve lent out over € 800 million since inception (2016) and have processed over € 7 billion in transaction volume. We're located in a monumental building in the city centre of 's-Hertogenbosch that also houses the Jheronimus Academy of Data Science (JADS). We are with around 60 people, split over Development, Data, Risk, Marketing and Sales.

What you'll be doing

In this role, you will drive impactful initiatives across various stages of the machine learning lifecycle, from building to deploying predictive models.

• Build and deploy predictive models trained on the financial data of our clients. 

• Own your impact - collaborate directly with risk teams, innovate freely, and shape our tech landscape without the oversight of a traditional product owner.

• Experiment with features to improve our modelling. 

• Bring projects to production, ensuring impactful contribution.

• Improve our code base and keeping our systems tidy and healthy.

• Work alongside a team of six data professionals, including machine learning engineers, analytics engineers, and data analysts.

• Develop yourself and your team.

Technology

We have a technology neutral mindset to engineering and believe in well-tested, robust code. We love open source but are not religious about any specific language or framework. We work with modern open source technology such as Polars, DuckDB, scikit-learn, uv, ruff, FastAPI and onnx. We are using Machine Learning models in production and are managing of all the infrastructure around these models that is needed for them to perform well. We’re big on continuous integration and deployment, automated testing and Kanban, pull-based processes.

We don’t have code monkeys. Instead, we give you a problem and trust you will come up with an outstanding solution. We prioritize sustainable work-life balance, allowing you to bring your best self to work every day. We do things our own way, we ship code every day and we take pride in our work.

Find out more on https://floryn.tech/

What you’ll bring

• Skilled in training and evaluating classic machine learning models, including regression, classification, clustering, and time-series forecasting.

• At least 3 years of hands-on experience in training and deploying machine learning models in production environments.

• Strong expertise in Python / R, and SQL.

• A focus on creating value rather than obsessing over hyperparameters.

• An analytical mindset with a critical approach to problem-solving.

Nice to have

• Experience with version control (we use git + GitHub).

• Experience with DevOps/MLOps technology (such as MLFlow, Docker, CI/CD, Testing).

• Experience with infrastructure engineering, particularly in AWS.

• Familiarity with data orchestration tools (e.g., Airflow, Prefect, Dagster).

Perks & benefits

• Good salary, pension contribution and 30 days paid time off.

• MacBook Pro and all high-end gear that you need.

• Enjoy a flexible work environment with options for both remote and in-office work.

• Travel comfortably by first-class rail or €0,21/km and parking.

• Daily ‘bourgondische’ lunch at the office.

• Generous budget to develop yourself with books, courses and conferences.

• Many team activities, from drinks to sporting events.

Application process

1. You apply by submitting your CV and optionally a cover letter.

2. First video / in-person meeting with our Head of Data.

3. A collaborative 3-hour in-office skills assessment to showcase your abilities in a real-world scenario.

4. Receive a final offer and start your journey with us.