About the role
Company Description We’re Checkout.com - you might not know our name, but we’re behind many of the digital experiences people use every day. When you book a holiday, order food, renew a subscription or check out online with brands like Spotify, Klarna, Uber Eats, TikTok, Sony, or eBay, there’s a good chance our technology powers the payment behind the scenes. At Checkout.com , we’re building where the world checks out - enabling over ten billion transactions every year for more than one billion shoppers globally. Our platform helps the world’s most ambitious businesses deliver seamless digital experiences at scale. We’re also building a company designed for people who want to do career-defining work. We move fast, think globally, and believe great teams are built by hiring exceptional people with conviction, curiosity, and a focus on impact. With 20 offices across six continents and London as our HQ, we’re shaping the future of fintech and we’re just getting started. 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. 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. How you’ll 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 5+ years of experience as MLOps /ML Engineer High proficiency 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 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 Additional Information Bring all of you to work We create the conditions for high performers to thrive, through real ownership, fewer blockers, and work that makes a difference from day one. Here, you’ll move fast, take on meaningful challenges, and be recognized for the impact you deliver. It’s a place where ambition gets met with opportunity, 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 you’re ready to grow and make a difference, you’ll be right at home here. It’s 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 it’s 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