🇵🇹 Lisbon

Engineering

Full-time

Machine Learning Engineer

The Data Domain comprises four teams: Data Science (DS; including ML Engineering); Data Engineering, Analytics Engineering, and Data Governance. In this central Domain, we enable Mollie and its Merchants to create value from data by providing a central data platform, data models, and machine learning (ML) models.


Your Opportunity

We are looking for a ML Engineer to join our growing team of Data Scientists (DSs) & Machine Learning Engineers (MLEs). Our team is set up as a central entity that provides advanced analytics capabilities across Mollie. We primarily develop predictive ML models that provide decision intelligence to our colleagues in various departments, such as Product, Operations, and Commerce. We also developed and now maintain a cloud-based ML Platform, which we use for both model development and production.

This is a hands-on role, where you will spend most of your time developing in Python together with our team of MLEs and DSs. 

This role is based at Mollie’s Lisbon Hub. You will be part of a geographically-distributed team (Amsterdam/Lisbon/Milan) that is comfortable collaborating virtually & hybrid. 


What you'll be doing

  • As a ML Engineer, you will be working closely with other ML Engineers, Data Scientists, and various engineers across Mollie. 

  • Contribute to the design and development of scalable, low-latency ML infrastructure and services at Mollie, including adding new functionality to our ML Platform.

  • Promote and implement best practices & standards in MLOps.

  • Bring models to production in collaboration with Data Scientists.

  • Evaluate feasibility of potential ML model development projects across Mollie.

  • Document MLE workflows and ensure compatibility with other systems at Mollie, including compliance with security standards (threat modeling).


What you'll bring

  • You have 3+ years of proven experience as an ML Engineer (or similar), including developing and maintaining ML Platforms and Model Pipelines.

  • You have advanced software engineering skills and love coding in Python. 

  • You are comfortable with at least one major cloud AI platform, preferably Google Cloud’s Vertex AI.

  • You have experience with containers and container orchestration, e.g. with Docker, Kubernetes, and Kubeflow.

  • You have experience:

  • Using Terraform or similar infrastructure-as-code tools.

  • Using (Py)Spark and managing Spark clusters.

  • You know your way around a linux shell and are comfortable with Git for version control.

  • You are familiar with the Model Development Lifecycle and common DS libraries, such as scikit-learn, pandas, shap, evidentlyai, and mlflow.

  • You are detail-oriented but can also quickly shift priorities if required.

  • You have solid presentation skills and can communicate to a wide variety of audiences.

  • You enjoy working collaboratively in a cross-functional & distributed team environment.

  • You are comfortable in an agile Way of Working, with Scrum, Kanban, or similar frameworks. 


Nice to have

  • Experience implementing streaming applications and related infrastructure.

  • Experience deploying Large Language Models.

  • Terraform Developer Certification

  • Google Cloud ML Engineer Certification

  • Experience in the financial services industry (banking or fintech)

  • M.Sc. or Ph.D. in Machine Learning or Computer Science

Benefits

Noise cancelling headphones

MacBook

Birthday off

Complimentary baby days

20 days working from abroad

22 holiday days

Commute allowance

Work from home budget

Bike lease plan

Internet allowance

Lunch voucher

Wellbeing program

Pension contribution

Health insurance

Bonus scheme

Equity plans

Referral bonus

Learning platform

Mentor program

Noise cancelling headphones

MacBook

Birthday off

Complimentary baby days

20 days working from abroad

22 holiday days

Commute allowance

Work from home budget

Bike lease plan

Internet allowance

Lunch voucher

Wellbeing program

Pension contribution

Health insurance

Bonus scheme

Equity plans

Referral bonus

Learning platform

Mentor program

How we hire

Step 1

Apply

Our Talent Acquisition team and hiring manager will review your application, and respond within 2 weeks.

Step 2

Screening call

If you seem like a Mollie-in-the-making, we’ll invite you to a screening call so we can learn more about each other.

Step 3

Are you the one?

You'll have two or more interviews. And if it's a highly technical role, we'll also assess the specific skills you'll need.

Diversity, Equity & Inclusion

At Mollie we embrace what makes you unique, and nurture a culture that feels like home. We celebrate diversity of people and perspectives every day and are proud to be an equal opportunity employer. We do not discriminate.

Every new Mollie is hired on the basis of qualifications, merit, and business need. We bring open hearts and open minds, we don’t judge each other for our differences, we embrace the unique traits that make our products and culture stronger.

There is an energy at Mollie that can’t be contained. We are proud to be here, and inspired by the problems we have left to solve. So come join the ride.

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