Staff Machine Learning Engineer, Financial Products

📋 Job Overview

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.

🏢 About 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.

🎯 The Role

The Financial Products org at Adyen is at the forefront of our evolution, building the foundational infrastructure that enables our customers to manage their finances, issue cards, and access credits and financing globally. Adyen is building a Machine Learning Engineering team in San Francisco focused on Credit Risk Modeling for Underwriting within Financial Products. This team will develop the models, scorecards, and production systems that enable Adyen to scale its credit products 100x. As a Staff Machine Learning Engineer you will design, productionize, and operate machine learning models and rule-based decision systems that power credit products. You will work across the full model lifecycle, from research and data analysis to training, deployment, monitoring, and continuous improvement.

✅ Key Responsibilities

• Develop and maintain scalable production ML pipelines for feature engineering, model training, validation, and deployment. Examples ML domains are: supervised and semi-supervised learning methods for inference on credit risk patterns;
• 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 CreditOps and data teams to integrate effectively with current tools, and shape priority for future tools;
• Support and encourage good engineering practices on product ML teams;

📌 Required Qualifications

• You have 8+ years of experience as an engineer working in the machine learning domain;
• You are a strong Python programmer and you have experience in Java.
• 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.

⭐ Desirable Experience

• You have experience on underwriting models or systems
• You have experience working with a Machine Learning ‘Feature Store’

🎁 Benefits

This is an exceptional opportunity to join a solid, established company with a startup mindset, characterized by small teams, direct communication, and work on important challenges. You’ll have direct access to massive global datasets (e.g., payments, identity data) and the ability to see your team's work have an immediate impact at scale. We offer an environment of ownership and speed, where a focused research team can make a significant difference. You will be at the forefront of bridging ML and fintech, shaping how these two critical areas intersect. We are looking for individuals who are eager to stay connected to the edge of ML innovation while ensuring we deliver practical value to our global platform. The annual base salary range for this role is $297,000 - $401,000, plus RSUs.

🛂 Visa & Eligibility

Adyen is an equal opportunity employer. We do not discriminate based on race, color, ethnicity, ancestry, national origin, religion, sex, gender, gender identity, gender expression, sexual orientation, age, disability, veteran status, genetic information, marital status or any legally protected status. All your information will be kept confidential according to EEO guidelines.