AI/ML Developer

We are looking for an AI/ML Developer to develop and integrate AI-driven capabilities into our enterprise cybersecurity platform. The role involves building intelligent solutions for security monitoring, threat detection, anomaly detection, risk analysis, and automation. 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).