Checkout.com

Senior Machine Learning Engineer

AWS Spark Python Machine Learning
Description

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, 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 number 9 on the Forbes Cloud 100 list and on Glassdoor’s list of Top 10 fintechs to work for. 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. So, join us to build tomorrow, today.

Job Description

As a Senior Machine Learning Engineer at Checkout.com in the ML Platform team, you will play a key role in the early design and development of our machine learning platform. You will contribute to the establishment of standards & architecture and collaborate with an ambitious group of engineers to increase the maturity level of our platform. 

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:

  • Develop and deliver solutions used across products such as Fraud Detection and Payment Optimization 
  • Build systems for training, deploying and monitoring machine learning models used in real-time inference 
  • Scale our feature store to more and increasingly complex use-cases both online and offline
  • Contribute to technical and architectural decisions that increase the maturity level of the platform
  • Actively promote critical thinking, to challenge and improve our systems and processes by leveraging past experience

Qualifications

  •  
  • Production experience with building and operating high-volume ML systems, including low-latency model and feature serving 
  • Experience with monitoring and observability of production ML systems, with a strong sense of ownership 
  • Proficiency in Cloud-based application development (we use AWS)
  • Experience with one or more of these technologies: Spark, Databricks, SageMaker, Vertex AI, Kubeflow, Seldon 
  • Versed in writing clear, production-ready Python code
  • Solid understanding of theoretical aspects of machine learning 
  • Growth mindset, always on the lookout for stretch challenges 
  • Excellent communication skills, ability to interact effectively with multidisciplinary teams
  • Experience dealing with data from complex domains (FinTech, Fraud Detection or Payments Processing are a significant plus)
  •  

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.

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