At Mangopay, our mission is to power the payment infrastructure and payment operations of the worlds biggest and most exciting marketplaces & platforms.

We provide marketplaces and platforms with powerful modular payment and regulatory solutions. Since 2013, we have enabled the success of some of the biggest names in e-commerce, retail, and cutting-edge platforms such as Vinted, Rakuten, Chrono24, La Redoute, Wallapop and over 2,500+ more. 

Our team of 400+ is spread across Europe, with offices in Berlin, Dublin, Luxembourg, London, Madrid, Paris, and Warsaw. In an environment where marketplaces and fintech ventures are thriving, were actively seeking exceptional individuals to tackle the challenges in our field and contribute to our growth. Our commitment to diversity is unwavering, and we are dedicated to promoting employee well-being, inclusivity, and equal opportunities. Joining Mangopay means you’ll be part of a dynamic, flexible, and rapidly growing team.

Mangopay is looking for a Senior ML Software Engineer with expertise in MLOps to join one of our Risk departments engineering teams. Our team is responsible for modern client-facing fraud prevention services, helping online merchants across diverse sectors like e-commerce, travel, crypto, and lending to maximize their risk management and customer acquisition investments. You will tackle a wide array of use cases, taking ownership of various code pieces and driving their direction. We foster a collaborative environment where everyone plays a crucial role.

What will you be responsible for?

• Develop, automate and optimize machine learning workflows, including CI/CD pipeline integration.
• Collaborate with Platform Engineers to establish the necessary infrastructure for efficiently executing MLOps processes.
• Work with data scientists to automate model training, tuning, and deployment.
• Ensure compliance with data security and privacy standards.
• Suggesting innovative enhancements to our AI initiatives

What would we like to see?

Must have:

• At least 3 years of professional experience in MLOps or Data Engineering.
• Intermediate proficiency in Python, including the scientific stack: Pandas, Numpy, and Scikit-learn.
• Intermediate understanding of cloud computing. Familiarity with machine learning services (e.g., AWS SageMaker, Azure ML, GCP Vertex AI).
• Proficiency in working with AWS, GCP, or Azure Cloud.
• Proficiency in containerisation technologies such as Docker, with a foundational understanding of container orchestration platforms like Kubernetes.
• Very good command of English.

Nice to have:

Familiarity with

• Kafka/PySpark/PyFlink.
• At least one orchestration and scheduling tool, such as Dagster, Prefect or Airflow.
• Data modelling tool like DBT/Dataform.
• One of the cloud-based data platforms (Snowflake, BigQuery, Databricks).

If this role sounds of interest to you, and matches your experience, get in touch via the apply button!

We care about equal employment opportunities, so all qualified applicants will receive equal consideration regardless of their race, colour, religion, sex, sexual orientation, gender perception or identity, national origin, age, marital status, protected veteran status, or disability status.