Machine Learning Engineer

Company Description

Checkout.com is one of the most exciting fintechs in the world. Our mission is to enable businesses and their communities to thrive in the digital economy. We’re the strategic payments partner for some of the best known fast-moving brands globally such as Wise, Hut Group, Sony Electronics, Homebase, Henkel, Binance, Klarna and many others. Purpose-built with performance and scalability in mind, our flexible cloud-based payments platform helps global enterprises launch new products and create experiences customers love. And it's not just what we build that makes us different. It's how.

We empower passionate problem-solvers to collaborate, innovate and do their best work. That’s why we’re on the Forbes Cloud 100 list and a Great Place to Work accredited company. And we’re just getting started. We’re building diverse and inclusive teams around the world — because that’s how we create even better experiences for our merchants and our partners. And we need your help. Join us to build the digital economy of tomorrow.

Job Description

The role

This role will see you join Checkout’s Fraud Detection product, where you will work on machine learning systems for providing near-real-time transaction fraud predictions.

You will join an ambitious team of data scientists and engineers who are working to deliver fraud detection ML models to Checkout.com’s merchants, at scale. Your work will move the needle within a product area that has high strategic importance to Checkout.com.

How you’ll make an impact

• Maintain distributed systems for training, deploying, and monitoring machine learning models.
• Maintain a feature store to materialize consistent ML features for training and serving.
• Write production-ready code (mostly Python) for model training and deployment.
• Participate in out-of-hours support.

Qualifications

What we’re looking for

• Strong engineering background, with a high attention to detail.
• Experience working with ML in production and/or have strong interest in MLOps / ML systems.
• Familiar with distributed data processing tools (e.g. Dask, Spark, Hadoop).
• Theoretical understanding of machine learning methods, particularly ensemble decision trees.
• Able to write simple, production-ready (and well-tested), Python code.
• Experience maintaining RESTful ML model APIs.
• Experience with workflow management tools (e.g. Airflow, Metaflow, Prefect).
• Experience with SQL databases and key-value stores (e.g. DynamoDB).
• Experience working with Docker for development and deployment.
• Experience using AWS as a cloud provider.
• Familiar with the unix shell, and shell scripting.
• Proven track record working in technical teams.

Additional Information

Apply without meeting all requirements statement 

If you don't meet all the requirements but think you might still be right for the role, please apply anyway. We're always keen to speak to people who connect with our mission and values.

We believe in equal opportunities

We work as one team. Wherever you come from. However you identify. And whichever payment method you use. 

Our clients come from all over the world — and so do we. Hiring hard-working people and giving them a community to thrive in is critical to our success.

When you join our team, we’ll empower you to unlock your potential so you can do your best work. We’d love to hear how you think you could make a difference here with us. 

We want to 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. We’ll be happy to support you.

Take a peek inside life at Checkout.com via

• Our careers page https://www.checkout.com/careers

• Our LinkedIn Life pages bit.ly/3OaoN1U 

• Our Instagram https://www.instagram.com/checkout_com/