Key Responsibilities:

- Design, develop, and deploy AI/ML models for cybersecurity applications.
- Research emerging AI techniques and their application to threat detection, malware analysis, fraud detection, and anomaly detection.
- Develop predictive models to identify and mitigate cyber threats.
- Analyze large-scale security datasets, logs, and network traffic to uncover attack patterns.
- Build intelligent automation for incident detection, investigation, and response.
- Collaborate with Security Operations Center (SOC), threat intelligence, engineering, and product teams to integrate AI-powered security solutions.
- Evaluate the effectiveness of AI models and continuously improve accuracy, performance, and scalability.
- Stay current with advancements in artificial intelligence, cybersecurity, and adversarial machine learning.
- Conduct experiments, publish research findings where appropriate, and contribute to innovation initiatives.
- Ensure AI systems comply with security, privacy, and regulatory requirements.

Required Qualifications:

- Master's or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, Cybersecurity, Data Science, or a related field.
- 3 years of experience in AI/ML research or development with a focus on cybersecurity.
- Strong programming skills in Python and experience with AI/ML frameworks such as PyTorch, TensorFlow, or Scikit-learn.
- Knowledge of cybersecurity concepts including malware analysis, network security, endpoint security, identity security, and threat intelligence.
- Experience with deep learning, natural language processing (NLP),



graph machine learning, or reinforcement learning.
- Familiarity with cloud platforms such as AWS, Azure, or Google Cloud.
- Experience working with large datasets, distributed computing, and data engineering tools.
- Solid analytical, problem-solving, and communication skills.

Preferred Qualifications:

- Experience with Large Language Models (LLMs), AI agents, retrieval-augmented generation (RAG), and generative AI security.
- Knowledge of adversarial machine learning and AI model security.
- Experience with SIEM, SOAR, EDR, and XDR platforms.
- Familiarity with MITRE ATT&CK;, Zero Trust architecture, and threat modeling.
- Security certifications such as CISSP, GSEC, CEH, or GIAC are a plus.
- Publications, patents, or open-source contributions related to AI or cybersecurity.

Technical Skills:

- Programming: Python, SQL, C , Java
- AI/ML: PyTorch, TensorFlow, Scikit-learn, Hugging Face
- Data: Pandas, NumPy, Spark
- Cloud: AWS, Azure, Google Cloud
- Security: SIEM, SOAR, IDS/IPS, EDR, Threat Intelligence
- DevOps: Docker, Kubernetes, Git, CI/CD

Key Competencies:

- AI research and innovation
- Cybersecurity expertise
- Statistical analysis and data modeling
- Critical thinking and problem-solving
- Collaboration and communication
- Continuous learning and adaptability

Success Metrics:

- Improved threat detection accuracy and reduced false positives.
- Faster incident detection and response times.
- Successful deployment of scalable AI-driven security solutions.
- Measurable improvements in cybersecurity resilience through AI innovation.

📌 Security Scientist - AI/ML Research (India)
🏢 Sampoorna Computer People
📍 India