As an ML (Machine Learning) Ops Engineer at Checkout.com in the ML Platform team, you will contribute to the development of scalable systems that enable real-time fraud detection and payment optimization.
## What you will do
- Build systems for training, deployment and monitoring of machine learning models used in our payment 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 guidance from talented engineers
## What we are looking for
- 5+ years of experience as MLOps/ML Engineer
- Strong ability to write 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
- Familiarity with 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 seeking challenging tasks
- Curiosity to tackle open-ended problems and learn from failures
We work with a hybrid working model with three days per week in the office.