As an ML Ops Engineer at Checkout.com in the ML Platform team, you'll contribute to developing scalable systems that enable real-time fraud detection and payment optimization.
## What you'll do
- Build systems for training, deployment and monitoring of machine learning models in our payments platform, at scale
- Scale our feature store for more and increasingly complex use-cases, both online and offline
- Deliver end-to-end features with full ownership under the guidance of talented engineers
## Requirements
- 5+ years of experience as MLOps / ML Engineer
- High competency in writing clear, production-ready Python code
- Experience with production ML models (online or offline) and standard MLOps practices
- Experience with monitoring and observability of production systems, with a strong sense of ownership
- Knowledge of cloud-based application development (we use AWS)
- Knowledge of 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 with different teams
- Growth mindset, always looking for challenging tasks
- Curiosity to tackle open problems and learn from mistakes
## What we offer
Flexible hybrid work model with three days per week in the office to support collaboration and connection.