Abnormal Blog
Jeshua Bratman
Former Head of Machine Learning
Jeshua Bratman is an expert in applied machine learning with over 10 years of experience developing ML products and ML platforms. He is a founding engineer of Abnormal Security and the former Head of Machine Learning. Prior to starting Abnormal, Jeshua built Twitter’s machine learning platform and developed models to detect and prevent abusive behavior on Twitter. Prior to Twitter, Jeshua built the AI engine that powered TellApart’s predictive marketing products. His academic background is in theoretical reinforcement learning and deep learning from the University of Michigan where he worked on his PhD.
Abnormal's fundamental job is to detect malicious emails like phishing and business email compromise attacks and other malicious events, such as suspicious sign-ins that indicate an account has been hacked.
Over the last three years building our ML-based cybersecurity products at Abnormal Security, I’ve benefitted enormously from discussions with colleagues in the ML space. This podcast aims to make some of those conversations available. In our second episode of Abnormal Engineering Stories...
It’s one thing to add machine learning and artificial intelligence features to an existing software platform. It’s quite another to build an entire company like Abnormal Security around machine learning technology, and to provide practical, everyday value to enterprise organizations.
Machine learning engineering is hard, especially when developing products at high velocity, as is the case for us at Abnormal Security. Typical software engineering lifecycles often fail when developing ML systems.
Developing a machine learning product for cybersecurity comes with unique challenges. For a bit of background, Abnormal Security’s products prevent email attacks—think credential phishing, business email compromise, and malware—and also...
At the core of all Abnormal’s detection products sits a sophisticated web of prediction models. For any of these models to function, we need deep and thoughtfully engineered features, careful modeling of sub-problems, and the ability to join data from a set of databases. For example, one type of email attack...
Sophisticated social engineering email attacks are on the rise and getting more advanced every day. They prey on the trust we put in our business tools and social networks, especially when a message appears to be from someone on our contact list, or even...