Machine Learning Engineer

London logo
Apply now Apply later

We're building the connected finance businesses deserve. Unleashing them with tomorrow's technology, today. Our flexible payments solutions help global enterprises — like Samsung, Deliveroo and Adidas — launch new products and create experiences customers love. And it's not just what we build that makes us different. It's how.
We liberate smart, passionate people to collaborate, innovate and do their best work — faster. That's why we're one of the most valuable fintech firms around. But we're just getting started. By cutting through financial complexity, we'll empower companies to change the world. Join us. Unlock your potential.
Build tomorrow, today.
This role will see you join Checkout’s Data Platform team, where you will work on machine learning systems for providing near-real-time transaction fraud predictions. Checkout’s Data Platform team is composed of engineers who build systems to enable product teams to be data-driven and maximize the amount of time they spend solving business problems rather than data infrastructure/implementation ones.You will join an ambitious team of data scientists and engineers who are working to deliver fraud detection ML models to’s merchants, at scale. Your work will move the needle within a product area that has high strategic importance to

Key Responsibilities:

  • Maintain distributed systems for training, deploying, and monitoring machine learning models.
  • Work on batch and real-time ingestions to make ML features available offline (for training) and online (in production).
  • Write production-ready code (mostly Python) for model training and deployment.
  • Participate in out-of-hours support.

About you:

  • Strong engineering background, with high attention to detail.
  • Experience working with, and scaling, machine learning 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.

Nice to have:

  • Experience with stream processing technologies (e.g. Kinesis, Kafka).
  • Familiar with profiling code and performance optimizations.
  • Open source contributions and/or personal software projects.
  • Experience with ETL tools like dbt.
  • Experience with C#.
What we stand for
At, everything starts with our values, including the experience we offer our people.
#AspireWe supercharge your professional growth with career development programs and leadership training. You can learn your way, with tailored pathways and online platforms. And be inspired at relevant conferences.
#ExcelWe don't stop at 'good' here. We strive for excellence amongst our teams every day and recognize colleagues who take it to the next level through our quarterly peer-nominated Hero awards.
#UniteWe're proud of our global connections and inclusive environment. So we champion this through our colleague-led community groups and celebrate many cultural events together.
Want to see us in action?
Take a peek inside here.
More about Checkout.comWe empower businesses to adapt, innovate and thrive with the connected payments they deserve. Our technology makes payments seamless. We provide the fastest, most reliable payments in more than 150 currencies, with in-country acquiring, world-class fraud filters and reporting, through one API. And we can accept all major international credit and debit cards, as well as popular alternative and local payment methods. launched in 2012, and we now have a team of 1000 people across 17 international offices. To date, we’ve raised a total of $830 million, with our recent Series C valuing us at $15 billion.
We believe in equal is an equal opportunities employer. We welcome applications from all members of society irrespective of age, sex, disability, sexual orientation, race, religion, or belief. We make recruiting decisions based on your experience, skills and personality. We believe that employing a diverse workforce is the right thing to do and is central to our success.
Job region(s): Europe
Job stats:  42  1  0
  • Share this job via
  • or

Explore more AI/ML/Data Science career opportunities