Security, Machine Learning at ThreatMark
Core
Building large-behavioral models to detect cyberthreats and financial fraud by analyzing user behavior (mouse movements, keystroke timings) and sensoric data, managing PB-scale data for real-time scoring.
Role type
Senior IC machine-learning engineer (fraud detection)
Builds
Real-time authentication/authorization flows and fraud detection features for banking clients
Domain
Cybersecurity + Financial Fraud
Deliverable
production ML models
Required skills
Python, Rust, TypeScript, Machine Learning, Real-time stream processing, Behavioral biometrics, Sensoric data analysis, AWS, Terraform, Redis, PostgreSQL
Preferred skills
Graph algorithms, Loops optimization, Sandbox exploitation, Malware detection
Technologies
Python, Rust, TypeScript, Redis, PostgreSQL, AWS, Terraform
Responsibilities
Develop low-latency stream processing engines, rewrite microservices to Rust, build new detection features, manage PB-scale data pipelines
Seniority
Senior, hands-on IC
