Engineer - Machine Learning

AI/ML Solution Development  

• Develop, test, deploy, and maintain Machine Learning and AI-based applications for LMS, Student Portal, and other academic systems. 
• Build intelligent automation solutions for student engagement, learning analytics, recommendation engines, chatbot support, assessment analytics, predictive analytics, and workflow optimization. 
• Support integration of AI/ML models with existing web applications and enterprise systems.

Product & Technology Collaboration 

• Work closely with the Product Manager to understand business requirements, change requests, enhancement needs, and digital transformation initiatives. 
• Coordinate with outsourced Tech Team for solution design, development timelines, testing, deployment, and issue resolution. 
• Participate in requirement gathering discussions with cross-functional teams including Academics, Operations, Student Support, Admissions, and Examination departments.

Data & Analytics 

• Build and maintain data pipelines, dashboards, and analytical models for academic and operational insights.  
• Analyze student behavior, learning patterns, engagement metrics, and system usage data to support decisionmaking. 
• Ensure data accuracy, security, and compliance while handling institutional data

Technology Enablement & Innovation 

• Research and recommend emerging AI/ML technologies relevant to online education and digital learning ecosystems. 
• Support implementation of Generative AI, NLP, recommendation systems, intelligent search, and automation initiatives. 
• Contribute to continuous improvement of user experience across digital platforms.

System Support & Business Continuity 

• Maintain technical documentation, model documentation, workflows, and deployment processes. 
• Act as an institutional backup resource for critical ML/AI systems developed by outsourced teams. 
• Support troubleshooting, bug fixing, and optimization of ML-enabled applications. 
• Ensure knowledge retention and continuity of critical technical processes within NCDOE.

Governance & Quality 

• Follow coding standards, testing protocols, version control practices, and information security guidelines. 
• Coordinate UAT (User Acceptance Testing) and support release management activities. 
• Ensure scalability, reliability, and performance optimization of AI/ML solutions.