Teams at Petra Security

Conduct quantitative and machine learning research for real-time account-compromise detection. Design, train, evaluate, deploy, and scale production models while working with customer attack data. Build systems for streaming pipelines, feature stores, high-performance databases, and distributed infrastructure. Contribute production-grade code, establish technical standards, and advance detection capabilities in a high-autonomy cybersecurity startup environment.

Design, train, evaluate, and deploy machine learning detection models that identify account compromise in real time. Move research models into scalable production systems, work with real-time data and distributed infrastructure, and architect solutions for rapid growth. Engage with customers to understand emerging attacks, shape technical direction, establish engineering standards, and raise the quality of a small, autonomous research and engineering team.

Build and scale Petra’s AI-powered cybersecurity detection platform, including real-time signal ingestion, behavioral analysis, and AI-driven decisioning. Architect distributed systems for rapid growth, improve production reliability and correctness, and serve as a senior technical voice on a small, autonomous engineering team. The role requires experience with scalable data-intensive systems and deploying machine-learning models in production.