Description

You will leverage artificial intelligence and machine learning to enhance threat detection, automate response systems, and build intelligent security frameworks.

Responsibilities

• Design and implement machine learning models to detect malware, phishing, intrusion, and APTs.
• Analyze large datasets from logs, endpoints, and network traffic to identify patterns and anomalies.
• Automate threat detection and response workflows using AI/ML models and tools.
• Develop behavior analytics (UEBA) models to profile users and entities for early threat identification.
• Integrate AI/ML models into existing SIEM, SOAR, or XDR platforms.
• Ensure AI systems are explainable, auditable, and compliant with data privacy standards.

Required Skills

• 3+ years of experience in cybersecurity engineering or threat detection.
• 2+ years of hands-on experience with machine learning and data science in a security context.
• Proficiency in Python and ML libraries including TensorFlow, PyTorch, and Scikit-learn.
• Experience with SIEM platforms such as Splunk or Elastic.
• Strong understanding of security operations, threat intelligence, and malware analysis.
• Solid knowledge of networking and operating systems including Linux and Windows.
• Ability to analyze logs and data lakes to identify attack vectors.
• Bachelor's or Master's degree in Computer Science, Cybersecurity, Data Science, or a related field.

Preferred Skills

• Experience with NLP techniques for phishing and email threat detection.
• Familiarity with cloud security platforms including AWS, Azure, or GCP.
• Knowledge of adversarial machine learning and model robustness testing.
• Security certifications such as CISSP, CEH, OSCP, or GIAC.

Key Skills

Education

Any Graduate