Staff Security ML Researcher
Core
Develop machine learning-driven approaches for threat detection, risk assessment, and security analytics to identify threats and model attacker behavior across complex enterprise environments.
Role type
Staff Security ML Researcher (hands-on IC)
Builds
Intelligent models, actionable insights, and customer-facing capabilities for breach containment and cyber risk reduction.
Domain
Cybersecurity + Machine Learning + Graph Analytics
Deliverable
production ML models
Required skills
Python, machine learning frameworks (Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch), statistical modeling, anomaly detection, behavioral profiling, clustering, classification, forecasting, graph-based analysis, SQL, model evaluation, feature engineering, handling imbalanced datasets
Preferred skills
graph neural networks, link prediction, cloud ML productionization (AWS, Kubernetes), risk-scoring systems, predictive analytics
Technologies
Neo4j, graph databases, AWS, Kubernetes, MITRE ATT&CK
Responsibilities
Design and deploy ML models for threat detection and risk prediction; analyze large-scale security datasets to identify attacker behaviors; develop threat scoring and risk assessment models; design and maintain scalable data pipelines for model training; partner with engineers to productionize models; collaborate with product teams to embed ML insights into customer experiences; explore emerging techniques in graph analytics and AI-driven threat detection.
Seniority
Staff, hands-on IC with strategic influence
