Staff Security ML Researcher (Cybersecurity)

Location: Sunnyvale, California, United States; on-site

Salary: $221,000–$265,000 annually

Company

hirify.global develops breach containment and Zero Trust Segmentation solutions that use AI-driven security analytics to protect hybrid multi-cloud environments.

What you will do

• Design, train, validate, and deploy machine learning models for anomalous behavior, threat detection, security risk, and breach likelihood.
• Analyze large-scale security telemetry to identify attacker behavior, emerging threats, and patterns aligned with MITRE ATT&CK.
• Build behavioral profiling, anomaly detection, clustering, classification, forecasting, threat-scoring, and risk-assessment models.
• Use graph-based analysis to model attack paths, quantify lateral movement risk, and recommend mitigation strategies.
• Build scalable data pipelines and partner with engineers to productionize reliable, observable ML and analytics systems.
• Collaborate with threat researchers, product managers, designers, and engineers to embed ML-driven insights into customer-facing capabilities.

Requirements

• 5+ years of experience in security analytics, threat research, detection engineering, data science, or machine learning.
• Strong Python skills and experience with data science or ML frameworks such as Pandas, NumPy, Scikit-learn, TensorFlow, or PyTorch.
• Experience deploying production machine learning or statistical models and working with large-scale security, networking, cloud, or infrastructure telemetry.
• Strong knowledge of model evaluation, feature engineering, experimentation, imbalanced datasets, and SQL.
• Experience applying ML or analytics to cybersecurity problems including anomaly detection, behavioral analysis, threat hunting, or risk assessment.
• Familiarity with MITRE ATT&CK and security telemetry sources, plus the ability to translate technical findings into product recommendations.

Nice to have

• 7–10+ years of experience across cybersecurity, machine learning, data science, or threat research.
• Graph-based security analytics using Neo4j, graph databases, graph algorithms, graph neural networks, or link prediction.
• Experience productionizing ML models in cloud environments using AWS, Kubernetes, or similar platforms.
• Experience with risk-scoring systems, recommendation engines, predictive analytics, or external threat intelligence feeds.
• Advanced degree, relevant publications or patents, open-source contributions, conference presentations, or certifications such as CISSP or GIAC.

Culture & Benefits

• Collaboration across the Office of the CTO, Security, Engineering, Product Management, and threat research teams.
• Opportunities to explore machine learning, graph analytics, AI-driven threat detection, and cyber defense research.
• Potential contributions to patents, technical publications, conference presentations, and thought leadership.
• Benefits may include medical, dental, and vision coverage; health and dependent savings accounts; life and disability programs; paid parental leave; retirement savings; equity opportunities; paid time off; and paid holidays.