Senior Machine Learning Engineer, Adyen

• You have 5+ years of experience as an engineer working in the machine learning domain
• You are a strong Python programmer
• You have experience with the full machine learning model lifecycle in production flows
• You have experience leveraging big data to create the pipelines needed to feed the models with appropriate data
• You have a strong understanding of good software engineering practices as well as data engineering and MLOps principles
• You have knowledge of data science, statistics and machine learning techniques
• You have strong familiarity with the standard data science toolkit in python, such as (py)spark, (Trino) SQL, Tensorflow, PyTorch, XGBoost/LightGBM, Pandas, MLFlow or similar MLOps frameworks, and Airflow
• You have knowledge/experience of working with ML infrastructure components with tools such as k8s, docker, airflow, argo-workflows, prometheus, grafana
• You have an experimental mindset with a launch fast and iterate mentality
• You proactively take the lead in projects, from ideation to deployment. You have experience working with a wide range of stakeholders and can clearly communicate complex outcomes over a wide range of audiences
• Studies show that women and members of underrepresented communities apply for jobs only if they meet 100% of the qualifications. Does this sound like you? If so, Adyen encourages you to reconsider and apply. We look forward to your application!

Desirable

• Adyen is looking for a Senior Machine Learning Engineer to join our team in Amsterdam, someone with experience of building and operating robust machine learning systems at scale in production environments. You will be responsible for designing, productionizing and maintaining machine learning services that power data products at Adyen
• Teams Currently Hiring:
• Optimise: Optimize Intelligence at Adyen is a specialized team of Machine Learning Scientists and Data Analysts focused on maximizing transaction success, minimizing transaction costs, and driving payment performance at a global scale. We build and scale advanced ML/DL solutions that operate over massive, complex decision spaces, determining the optimal path for every single transaction in real time. Our systems evaluate high-dimensional data streams to dynamically select the optimal authentication methods, apply smart payment message optimizations, and orchestrate intelligent transaction routing. Our models live-score millions of daily transactions, balancing coupled cost and performance objectives simultaneously
• If you are passionate about solving intricate combinatorial challenges and pushing the boundaries of adaptive decision-making systems, join us in shaping the future of payments
• Identity and Verification Decisioning: This is an opportunity to help define how Adyen makes identity decisions at global scale
• The team sits at the intersection of machine learning, distributed systems, fraud prevention, compliance, and customer experience. Rather than optimizing isolated models, you'll help build the intelligence that determines how millions of businesses and individuals are verified throughout their lifecycle
• You'll join a newly formed engineering team, giving you significant influence over the technical direction, architecture, and ML strategy from an early stage. Your work will directly impact fraud prevention, regulatory compliance, operational efficiency, and customer onboarding experience
• Payments Core Data - Disputes: Adyen is building a dispute intelligence function. The team will be building ML and AI applications to make our dispute product more intelligent. We’re looking for someone with an optimization mindset, looking for an opportunity which allows for continuous experimentation and improvement by enriching the algorithms context (structured and unstructured data)
• The challenge for the person refers to a greenfield opportunity, allowing for Disputes Machine Learning and AI use cases to be built from the ground up. You’ll be working side-by-side with both the Data Engineers and Machine Learning Scientists with respect to disputes data, and with the disputes engineering team who are owning the dispute product as a whole
• AML Tech: Adyen's Anti-Money Laundering team processes massive transaction volume to detect complex financial crime and cover a wide range of customer risks. We currently run a hybrid stack of business rules and machine learning models - with a clear mission to systematically reduce our dependence on static rules and transition to a modern, model-first detection engine
• As a Senior Machine Learning Engineer, you'll play a critical role in this evolution. You will architect scalable batch processing pipelines, tackle hard technical challenges like extreme class imbalance and incomplete ground truth, and drive production ML systems that will make financial world safer for everyone
• In this role, you will: Develop and maintain production ML pipelines for data ingestion, training, validation, and deployment. Examples ML domains are: on-line learning algorithms to pick the best optimization decision in a changing environment, clustering algorithms to group customers/shoppers, supervised and semi-supervised learning methods for inference on risk patterns or graph analysis, representation learning for behavior prediction and monitoring, Anti-Money Laundering (AML) systems and real-time anomaly detection based on time-series modeling
• Identify and fix performance bottlenecks in ML training and inference (memory consumption, online latency, training time etc.)
• Collaborate with software engineers to integrate ML solutions into products and services
• Collaborate with data scientists to transition research prototypes into scalable solutions
• Collaborate with MLOps and platform teams to integrate effectively with current tools, and shape priority for future tools
• Support and encourage good engineering practices on product ML teams

• Ensuring a smooth and enjoyable candidate experience is critical for us. We aim to get back to you regarding your application within 5 business days. Our interview process tends to take about 4 weeks to complete, but may fluctuate depending on the role