Staff Machine Learning Engineer, Financial Products
About this role
Engineers who combine strong machine learning and production engineering experience with sound judgment in high-integrity financial systems will thrive in this position. Adyen is establishing a Machine Learning Engineering team in San Francisco focused on Credit Risk Modeling for Underwriting within the Financial Products organization. This group builds the models, scorecards, and production systems designed to scale credit products globally.
Working across the full model lifecycle, the person in this role will design, productionize, and operate machine learning models and rule-based decision systems. Responsibilities include building continuous data flywheels that refine underwriting choices while balancing rapid product delivery with robustness, explainability, and scale. Collaboration with product, engineering, risk, and data teams is central to delivering these capabilities for major global businesses.
What you will do
- Develop and maintain scalable production machine learning pipelines for feature engineering, model training, validation, and deployment.
- Identify and fix performance bottlenecks in machine learning training and inference such as memory consumption, online latency, and training time.
- Collaborate with software engineers to integrate machine learning solutions into existing products and services.
- Partner with CreditOps and data teams to integrate effectively with current tools and shape priorities for future tooling.
- Support and encourage good engineering practices across product machine learning teams.
What you need
- Bring over 8 years of experience as an engineer working in the machine learning domain.
- Demonstrate strong programming proficiency in Python and practical experience with Java.
- Possess hands-on experience with the full machine learning model lifecycle in production flows.
- Leverage big data to create the data pipelines required to feed models appropriately.
- Maintain a strong understanding of software engineering practices, data engineering, and MLOps principles.
- Apply deep knowledge of data science, statistics, and machine learning techniques.
- Utilize standard data science and MLOps tools such as PySpark, SQL, TensorFlow, PyTorch, XGBoost, Pandas, MLflow, and Airflow.
Nice to have
- Experience on underwriting models or systems
- Experience working with a Machine Learning Feature Store
Benefits
- RSUs in addition to annual base salary
- Global mobility options with future relocation conversations to Amsterdam or Madrid offices
Skills and tech stack
Questions candidates ask
Is this a remote role?
Adyen is an office-first company that values in-person collaboration and does not offer remote-only roles. This position is based out of the San Francisco office.
What is the salary range for this position?
The annual base salary range for this role is $297,000 to $401,000, plus RSUs.
What does the hiring process look like?
The company aims to respond to applications within 5 business days. The interview process generally takes about 4 weeks to complete, though this may fluctuate depending on the role.