AIML Developer

The candidate will work closely with engineering and product teams to apply AI/ML techniques to real-world cybersecurity challenges particularly in Privileged Access Management (PAM) Identity Security and user behaviour analysis.

Key Responsibilities

• Design develop and implement ML models for intrusion detection phishing detection and anomalous access behaviour.
  
• Analyse security logs authentication data network traffic and threat intelligence feeds.
  
• Perform data preprocessing feature engineering and model evaluation.
  
• Implement supervised unsupervised and deep learning techniques.
  
• Develop solutions for anomaly detection User and Entity Behaviour Analytics (UEBA) risk scoring and threat detection.
  
• Integrate AI/ML models into existing enterprise applications and security platforms.
  
• Develop and consume REST APIs for AI-powered capabilities.
  
• Optimize model performance accuracy and scalability.
  
• Conduct experiments validate results troubleshoot model issues and improve detection capabilities.
  
• Collaborate with product engineering and cybersecurity teams to translate business and security requirements into AI-driven solutions.
  
• Document experiments implementation approaches and model performance.
  
  

Required Skills and Experience

• Bachelors or Masters degree in computer science AI/ML Data Science Cybersecurity or a related field.
  
• 2 years of experience in AI/ML development Python/C# development or related software engineering.
  
• Strong programming skills in Python or C#.
  
• Good understanding of Machine Learning statistics and data analysis.
  
• Hands-on experience with Scikit-learn PyTorch or TensorFlow.
  
• Experience with Pandas and NumPy for data processing.
  
• Knowledge of supervised/unsupervised learning anomaly detection and model evaluation.
  
• Experience with REST APIs and backend development.
  
• Familiarity with Windows and Linux environments.
  
• Knowledge of Git and software development practices
  

Preferred (Nice to Have)

• Understanding of cybersecurity concepts such as network security SIEM SOC and threat intelligence.
  
• Exposure to IAM PAM and Identity Security.
  
• Experience analysing security logs authentication events and system telemetry.
  
• Familiarity with NLP deep learning and time-series analysis.
  
• Exposure to Generative AI LLMs and AI-powered automation.
  
• Basic knowledge of Docker and cloud platforms (AWS/Azure).