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 shit 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 Engineers are responsible for developing and operationalizing online and offline algorithms which integrate with Revolut’s server layer. They are skilled in software engineering, machine learning, network science and applied mathematics. They also possess a passion for building solutions and have a strong aptitude for data technologies.
You will work with the Financial Crime - Transaction monitoring team. We are a full stack team of data engineers, ML engineers, data scientists, backend engineers and financial crime specialists who are solving some of the hardest anti-fraud and anti-money laundering problems in the world. Our team builds artificial intelligence (AI) driven systems that continuously learn anomalous patterns typical of fraud. In this regard, we need a machine learning engineer to join our team and build new models to detect cloning of Revolut cards, stolen cards or bank accounts being linked to a Revolut account. If you love pitting your wits against an intelligent adversary by utilizing AI, then this is your gig!
WHAT YOU’LL BE DOING ✍️
You will be responsible for building new machine learning models to solve anti-fraud or anti-money laundering. Our machine learning engineers are end-to-end practitioners which implies they are responsible for coming up with an idea, prototyping the model using Jupyter notebook, implementing it in our data pipeline and measuring its impact in production.
You will work alongside a team of 10+ machine learning engineers and data scientists in Financial Crime and come up with innovative new signals and embeddings. At Revolut, we are firm believers in measuring and rewarding for success and your KPIs will be dictated by how much impact your models are having to our bottom line (fraud rate) while not compromising our good users’ experience.
Our data stack is Python in the backend with Exasol as our data warehouse. We are hosted on Google Cloud Platform and our team relies heavily on DataFlow, Big Query, Apache Beam, Apache Flink & Airflow for their machine learning pipelines.
WHAT SKILLS YOU'LL NEED 📖
Proficient with Python and able to push code into production
1+ year(s) experience in applied machine learning/network science solutions via internships or full-time roles
Bachelor's/Master's/PhD in STEM (Mathematics, Computer Science, Physics, Engineering, Economics)
Quick learner with an ambitious and results driven personality
Working well as part of a team in a fast-paced environment
Excellent communication and organizational skills
You’ll get to work in one of the hottest and fastest growing tech startups in the world right now
We’ll arm you with all of the latest tech equipment
Competitive salary & equity
29 days of holiday (excluding bank holidays)
Private pension plan
Free Revolut Metal subscription
Fresh juice & soda all day long