Senior Machine Learning Engineer

Employer
Checkout.com
Location
UK
Salary
Competitive
Closing date
9 Jul 2021

View more

Sector
Technology & New Media
Contract Type
Permanent

Job Details

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.

*About the role:*
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. Checkouts Data Platform team is composed of engineers who build systems to enable product teams to be data-driven and maximise 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 Checkout.com's merchants, at scale. Your work will significantly move the needle within a product area that has high strategic importance to [Checkout.com](http://checkout.com/).

*Responsibilities:*

* Maintain infrastructure to train, deploy, and monitor machine learning models
* Develop batch and realtime processing pipelines 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
* Experience working with, and scaling, machine learning systems
* 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 distributed data processing tools (e.g. Spark, Dask, Hadoop)
* 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#

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* Competitive Salary & Performance Bonus
* Cutting Edge Technology & Latest IT tools
* Company retreat (surprise annual trips)
* Flexible working, 24 days of paid leave and Birthday off
* Season Ticket Loan, Cycle to Work Scheme, comprehensive benefit plans
* Internal community groups and cultural events
* Employee-led community outreach, payroll giving and a volunteering day
* A global wellness programme and private health insurance
* Tailored career development and learning pathways
* Peer recognition program and quarterly Hero Awards
TBCMachine Learning, PythonMachine Learning, Python

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