MLOps Engineer

This is Adyen

Adyen provides payments, data, and financial products in a single solution for customers like Meta, Uber, H&M, and Microsoft - making us the financial technology platform of choice. At Adyen, everything we do is engineered for ambition.

For our teams, we create an environment with opportunities for our people to succeed, backed by the culture and support to ensure they are enabled to truly own their careers. We are motivated individuals who tackle unique technical challenges at scale and solve them as a team. Together, we deliver innovative and ethical solutions that help businesses achieve their ambitions faster.

MLOps Engineer to join MLOps team

Adyen is seeking a MLOps Engineer to join our central MLOp team, which is responsible for building platforms and tools for all of our data science teams. In this role, you will play a crucial part in shaping the MLOps ecosystem at Adyen, serving a variety of machine learning and statistical models for both real-time and batch predictions — from optimizing payments to combating fraud.

Note: In this role, you won’t be building machine learning models yourself. Instead, your focus will be on enabling and supporting the teams who are developing them.

What you'll will be doing:

• Own, develop, deploy and operate tooling and services around MLOps:
• Performant model training and tracking.
• Safe, stable and performant machine learning model deployment in both real-time and batch flows, considering latency, reliability and scalability.
• Experiment tracking, validation and hyperparameter optimization runs
• Model monitoring for downtime, latency, and drifts.
• Ensuring scalability of the MLOps infrastructure and bringing MLOps maturity to the next level
• Building tools to democratize machine learning practices at Adyen. Work closely with product machine learning teams to identify their pain-points, way of working.

Who you are

• 2+ years of professional experience as a DevOps Engineer, MLOps Engineer, ML Engineer, Data Engineer
• You have strong software development skills, including: version control (e.g. Git and preferable on Gitlab), coding best practices, debugging, unit and integration testing.
• You have experience with the full machine learning model lifecycle in production flows.
• You have great knowledge of MLOps architectures and practices.
• You are very proficient in python
• You have a very good understanding of software engineering practices
• You have a good understanding of machine learning algorithms, and specifically dependencies on engineering and their lifecycle.
• You have the ability to diagnose and resolve model performance, scalability, and deployment issues.
• You have strong familiarity with the standard MLOps toolkit, such as (py)spark, MLFlow or similar MLOps frameworks, Airflow
• You have an experimental mindset with a launch fast and iterate mentality.
• Team player with strong communication skills, and are able to convey complex outcomes to a wide range of audiences.
• You are adept at collaborating with cross-functional teams and driving best practices.

Desirable additional qualifications:

• Proficiency with observability tools, such as: Prometheus, Logsearch, Kibana and Grafana.
• Experience in platform engineering and k8s, argoCD, helm is a plus
• Knowledge of kafka or any other streaming framework is a plus
• Knowledge of front end and/or java is a plus
• Experience in working with feature store is a plus
• Experience with setting up and managing GPUs for Accelerated Deep Learning is a bonus

This role is based out of our Amsterdam office. We are an office-first company and value in-person collaboration; we do not offer remote-only roles.

Tech careers

Our engineers are building the first financial technology platform that combines payments, data, and financial services. We’re looking for more talented problem solvers to help us address a unique set of challenges.