We are looking for someone who loves cyber security, machine learning, and big data, and at the same time appreciates a polished product with beautiful UI and developer-friendly API:s.
You will be building models for verifying users based on their browsing behavior, mouse movements, keystroke dynamics, location changes and device properties – i.e. primarily unsupervised learning and anomaly detection. One of the major challenges is to follow users between desktop and mobile devices, as well as distinguishing between two individuals even though they're using the same device.
You will also be responsible for architecting our streaming machine learning platform using open-source tools such as Spark, Kafka, Hadoop, Cassandra, etc.
Experience with information security or fraud prevention is a big plus.
Castle uses state-of-the-art machine learning to protect web and mobile apps from user account fraud. Users are profiled based on their typing patterns, mouse movements, device characteristics, browsing patterns, and hundreds of other signals. When something suspicious occurs, both the administrator and the user are alerted and can immediately take appropriate action, such as locking the account or having to go through additional verification.
Every line of code that you write will have a great impact. Every suggestion you make that can make our product perform better (ms, ROC, UX or $) has the potential to take the company a huge step forward. You will make a difference!
When it comes to company culture, building a diverse and inclusive team is at the heart of Castle. We look for voices unlike our own because they help us learn and expand our perspective. It's depressing to see inequality and exclusion as the defaults of the security industry. Without intentional effort, we will inherit those failings and worsen the problem.