Staff Machine Learning Engineer (Financial Products)

Join Adyen, a leading global payment company, as a Staff Machine Learning Engineer in San Francisco. In this role, you will be at the forefront of our financial products evolution, developing models and systems that enable us to scale our credit products. You will work across the full model lifecycle, collaborate with various teams, and support good engineering practices. This position offers a range of benefits, including a global exchange program, weekly happy hour, healthy lunches, and more.

This role is ideal for an engineer who combines strong machine learning and production engineering experience with sound judgment in high-integrity financial systems

We are looking for engineers with a customer-problem-first mindset and experience building reliable ML systems in production

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!

Responsibilities

• Design, productionize, and operate machine learning models and rule-based decision systems that power credit products.
• Develop and maintain scalable production ML pipelines for feature engineering, model training, validation, and deployment.
• Collaborate with software engineers to integrate ML solutions into products and services, and support good engineering practices on product ML teams.

Requirements

• You are a strong Python programmer and you have experience in Java
• You have a strong understanding of good software engineering practices as well as data engineering and MLOps principles
• You have 8+ years of experience as an engineer working in the machine learning domain
• 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
• 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 an experimental mindset with a launch fast and iterate mentality
• You have knowledge/experience of working with ML infrastructure components with tools such as k8s, docker, airflow, argo-workflows, prometheus, grafana
• 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 knowledge of data science, statistics and machine learning techniques
• You have experience working with a Machine Learning ‘Feature Store’

Preferred

• You have experience on underwriting models or systems

Pay

USD 297,000 - 401,000