AI/ML 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.
  
  

Requirements

Required Skills and Experience 

• Bachelor's or Master’s 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).