Machine Learning Engineer I

Checkout.com • Amsterdam, NY

81d • Hybrid

About The Position

As a Machine Learning Engineer at Checkout.com in the ML Platform team, you will contribute to the development of scalable systems that power real-time fraud detection and payment optimization. This is your opportunity to grow alongside top-tier engineers while making a tangible impact on millions of transactions globally. The solutions that you will be building will power our stack of value added services in the Payments Performance area. We're a growing team in an expanding area within the company and we're looking for individuals who have strong ownership, are passionate about productionising ML and have a pragmatic approach to converting big problems into smaller iterations to constantly deliver value.

Requirements

• Proficiency in writing clear, production-ready Python code
• Familiarity with production ML models (online or offline) and standard MLOps practices
• Familiarity with monitoring and observability of production systems, with a strong sense of ownership
• Familiarity in Cloud-based application development (we use AWS)
• Familiarity with one or more ML frameworks and technologies: scikit-learn, xgboost, TensorFlow, PyTorch, Spark, Databricks, SageMaker, Vertex AI, Kubeflow, Seldon, Triton
• Strong communication skills, able to express ideas clearly and collaborate across teams
• Growth mindset, always on the lookout for stretch challenges
• Curiosity to tackle open-ended problems and learn from failures

Responsibilities

• Build systems for training, deploying and monitoring machine learning models used in our payments platform, at scale
• Scale our feature store to more and increasingly complex use-cases both online and offline
• Deliver end to end features with full ownership under mentorship of talented engineers

Benefits

• Hybrid working model offers flexibility, with three days per week in the office to support collaboration and connection

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Industry: Furniture, Home Furnishings, Electronics, and Appliance Retailers
• Number of Employees: 1,001-5,000 employees