Company Description We99re Checkout.com 60you might not know our name, but companies like eBay, ASOS, Klarna, Uber Eats, and Sony do. That moment when you check out online? We make it happen. Checkout.com is where the world checks out. Our global network powers billions of transactions every year, making money move without making a fuss. We spent years perfecting a service most people will never notice. Because when digital payments just work, businesses grow, customers stay, and no one stops to think about why. With 19 offices spanning six continents, we feel at home everywhere 60 but London is our HQ. Wherever our people work their magic, they99re fast-moving, performance-obsessed, and driven by being better every day. Ideal. Because a role here isn99t just another job; it99s a career-defining opportunity to build the future of fintech. Job Description As a ML (Machine Learning) Ops 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. We99re a growing team in an expanding area within the company and we99re 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. How you99ll make an impact - 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 Qualifications - 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 Bring all of you to work We create the conditions for high performers to thrive 60 through real ownership, fewer blockers, and work that makes a difference from day one. Here, you99ll move fast, take on meaningful challenges, and be recognized for the impact you deliver. It99s a place where ambition gets met with opportunity 60 and where your growth is in your hands. We work as one team, and we back each other to succeed. So whatever your background or identity, if you99re ready to grow and make a difference, you99ll be right at home here. It99s important we set you up for success and make our process as accessible as possible. So let us know in your application, or tell your recruiter directly, if you need anything to make your experience or working environment more comfortable. Life at Checkout.com We understand that work is just one part of your life. Our hybrid working model offers flexibility, with three days per week in the office to support collaboration and connection. Curious about what it99s like to be part of our team? Visit our Careers Page to learn more about our culture, open roles, and what drives us. For a closer look at daily life at Checkout.com, follow us on LinkedIn and Instagram.