Machine Learning engineer

Nmbrs is looking for a Machine Learning Engineer to join our Lisbon team. Ready to leverage your ML expertise in a fast-growing payroll tech company? In this role, you'll drive the development of data-driven models that bring our ambition of a 100% Self-Driving Payroll a bit closer to reality. Working as the ML specialist within a dedicated AI-focused engineering team. Ready to transform complex data into insights that shape real business decisions?

Time to grow. Time to thrive.

We are Nmbrs. We build smart business software that removes unnecessary complexity for SMEs and the professionals who support them. Nmbrs brings together four established product organisations—Payroll, Accounting, Invoicing and Reporting—with teams across the Netherlands, Sweden and Portugal.

We are one brand with a shared ambition, while continuing to work from the expertise and strengths of our individual organisations. We join forces where it makes sense, while keeping teams, expertise and decision-making close together.

For this role, you’ll join Nmbrs Payroll in Lisbon, working closely with the colleagues in your local team while being part of the wider Nmbrs organisation.

Your role

As a ML Engineer, you’ll play a pivotal part in building advanced machine learning solutions. Ranging from salary benchmarking and predictive analytics to anomaly detection, all leveraging our extensive payroll data. Your work will help drive Nmbrs toward our vision of a self-driving payroll application.

Your impact

•  Drive the development of data-driven models (from salary benchmarking to anomaly detection) that bring Nmbrs Payroll closer to a 100% Self-Driving Payroll.

• Design and build supervised and unsupervised models (regression, classification, Random Forest, Gradient Boosting, Neural Networks) to solve real payroll problems.

• Turn raw payroll data into clean, well-engineered features that make your models accurate and reliable, using tools like Pandas and NumPy.

• Query and manipulate large volumes of data in SQL Server to fuel model development and analysis.

• Build and maintain scalable Python APIs (e.g., FastAPI) to deploy your models into production and integrate them into the wider product.

• Deploy and maintain ML models in cloud environments, ensuring they keep performing reliably as data and business needs evolve.

• Build and maintain automated ML pipelines that keep data flowing and models retraining with minimal manual intervention.

• Implement MLOps best practices, including CI/CD pipelines in Azure, so models can be shipped, monitored, and improved continuously.

You bring

• Degree in Computer science, Data science, Mathematics or any engineering related field.

• Experience building and maintaining scalable Python APIs (e.g., FastAPI) to deploy ML models into production.

• Experience implementing MLOps best practices, including CI/CD pipelines for ML models in Azure.

• Comfortable working independently, you'll be the only ML specialist on the team, so you're used to owning your work end to end.

• Fluency in English.

We offer

• A salary range of 3000€ to 4500€ gross per month (excluding holiday allowance), depending on your experience.

• Health insurance.

• Nmbrs is a flat organization where you get the freedom and responsibility to do what you’re good at and make an impact in a flexible, agile working environment.

• A personal coach who supports your personal and professional growth, plus an annual training budget.

• A healthy work-life balance: at Nmbrs, full-time means a 4-day workweek, giving you an extra day for what matters most to you.

• Hybrid working.

• As part of Visma, you get access to a wide range of development opportunities, including training, events and professional networks.

• The opportunity to spend up to 4 months on an exchange in our Amsterdam office.

• A pet-friendly workplace, feel free to bring your four-legged friend along.

Application process

1. Equalture assessment – You start with a series of neuroscience-based games via Equalture.

2. Cultural interview – An online conversation with one or two of our recruiters to get to know each other and see if there's a good cultural match.

3. Technical challenge.

4. Technical interview – You'll meet two colleagues from your team who will dive deeper into your knowledge, experience, and approach.

5. Final interview – A last conversation with our Tech Lead about the role, your ambitions, and what a potential collaboration could look like.