A LITTLE ABOUT US 🤔
From clunky apps to hidden fees, banking is broken. So we decided to build a company from the ground that would challenge the bigger players and reinvent how people interact with their money — for the better.
Traditional banks are slow and expensive. Realistically, you’re nothing but a number to them with dollar signs attached. So, one continent at a time, we plan on changing this.
OUR CULTURE 👫
To put it bluntly — it’s about getting s**t done and owning what you do. We don’t hide behind fancy job titles or set up bureaucratic processes. Instead we treat our people equally, fairly and give them a ton of freedom and autonomy to create something awesome.
We make mistakes, we learn from them and we back everything up with data and logic.
In three years, we’ve grown to over 700 people and we’re adding around 30 new additions each month. From engineers to marketers, we’re on the hunt for exceptional talent to help us scale our business and get Revolut in the hands of millions of people everywhere.
WHAT WE NEED 🚀
Our Machine Learning Platform Engineers are responsible for developing robust and scalable systems to accelerate our Data Science and Machine Learning functions. They have strong backgrounds in software engineering (full stack or back-end only) and some familiarity with the workflows of Data Scientists and ML Engineers. They are natural enablers and consistently aim to reduce technical debt associated with research and implementation.
We are currently building out our internal research platform and we need strong full stack engineers to contribute. Our research platform will be a cohesive interface to support model prototyping, workload execution (training/validation/prediction) and monitoring of productionized algorithms. We have adopted JupyterHub on Kubernetes as our tools of choice and we need you to build the functionality required to support this vision.
WHAT YOU'LL BE DOING ✍️
You will sit within our Product · Data · Research Platform team and you will be collaborating with our Data Scientists and Machine Learning Engineers in order to build and maintain our research platform.
Here are some of the things you will be working on:
- Building a beautiful UI integration in JupyterLab to support intuitive browsing/sharing of research projects
- Developing solutions to support collaboration, versioning and standardization of Jupyter notebooks
- Designing and integrating systems to support on-demand provisioning and remote notebook execution nodes in Kubernetes
- Ensuring our solutions can serve hundreds of users from a variety of backgrounds: Data Scientists, Machine Learning Engineers, Analysts, and even Product Owners
WHAT SKILLS YOU’LL NEED
Bachelor’s/Master’s/PhD in STEM (Mathematics, Computer Science, Physics, Engineering)
2+ years experience in full stack development with Python and JS
Deep knowledge of GCP’s data technologies and ability to build systems on Kubernetes
Demonstrated rigor in writing clean/understandable code and automated testing
Experience with open-source technologies: Kafka, Beam, Flink
Passion for enabling and building solutions to reduce technical debt
SQL - Exasol, PostgreSQL, BigQuery
NoSQL - DataStore, CouchDB, Redis
Versioning - GIT, Jira, or similar
Contributions to Project Jupyter
Interest in applications of Data Science and Machine Learning
Experience with prototyping and sketching