ML Engineer - Cybersecurity AI Platform
📍 Location : Remote / Hybrid
💼 Employment Type : Full-time & Part-time opportunities available
🎓 Education : Bachelor's degree required | Master's & PhD students encouraged to apply
🔒 Stealth Mode Startup
About the Opportunity
We're a well-funded stealth mode startup revolutionizing security operations with autonomous threat correlation technology. Our platform uses advanced AI to automatically connect the dots across disparate security systems, enabling security teams to detect and respond to sophisticated threats that traditional tools miss. Join us at the ground floor as we build the future of intelligent security operations.
What You'll Do
- Design and implement ML models for autonomous correlation of security events across heterogeneous systems and data sources
- Develop deep learning architectures that identify complex attack patterns and threat relationships without human intervention
- Build production-grade model training pipelines with automated calibration for evolving threat landscapes
- Create algorithms that synthesize multi-source threat intelligence into actionable security insights
- Optimize inference performance for real-time correlation and detection at enterprise scale
- Deploy and maintain large-scale models on modern hardware architectures in distributed environments
What We're Looking For
Required :
Bachelor of Engineering (B.E.) or Bachelor of Technology (B.Tech.) degree (completed or in final year)Strong foundation in neural networks, ensemble methods, and time-series analysisExperience working with security data (logs, network traffic, endpoint telemetry)Proven track record of implementing ML models (academic projects, internships, or production)Expertise in performance optimization for real-time ML systemsProficiency in modern ML frameworks (PyTorch, TensorFlow, etc.)Strong programming skills in Python and experience with distributed systemsBonus :
Currently pursuing Master's or PhD from a reputed institutionExperience with graph neural networks or relational learningKnowledge of SIEM, EDR, and other security operations technologiesUnderstanding of kill chains, MITRE ATT&CK, and threat intelligence frameworksExperience with anomaly detection and unsupervised learning techniquesPublications or contributions to ML / security research