NMIMS
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We are SVKM’s NMIMS Centre for Distance and Online Education (NCDOE) - India’s Premier Institution for with core focus on Distance & Online learning. Visit us at https://online.nmims.edu/about-us/ for more information.
The ML Engineer will support the Centre for Distance & Online Education (NCDOE) in designing, developing, implementing, and maintaining AI/ML-enabled solutions across the Learning Management System (LMS), Student Portal, and other in-house digital platforms. The role will work closely with the Technology Team, Product Manager, and other business stakeholders to drive technology-enabled innovation, automation, analytics, and intelligent learning solutions
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.
Individual Contributor Role.
Strong understanding of Machine Learning concepts, algorithms, model development lifecycle, and AI/ML application deployment.
Hands-on experience in Python and ML frameworks/libraries such as TensorFlow, PyTorch, Scikit-learn, Pandas, NumPy, etc.
Knowledge of NLP, Generative AI, Recommendation Systems, Predictive Analytics, Deep Learning, APIs, database systems, and integration architecture.
Familiarity with cloud platforms, version control tools, deployment environments, SQL, data visualization, and analytics tools.
Strong analytical, problem-solving, and critical thinking abilities with capability to convert business requirements into technology solutions.
Good stakeholder management, coordination, documentation, and communication skills.
Ability to work collaboratively with cross-functional teams including Product, Technology, Academics, Operations, and external vendors.
High ownership mindset with focus on reliability, continuity, process improvement, and institutional knowledge retention.
Attention to detail and quality orientation.
Ability to manage multiple priorities, timelines, and deliverables in a dynamic environment.
Adaptability, accountability, and proactive approach towards problem-solving and execution.
Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence / Machine Learning, Information Technology or related decipline.
Certifications or specialization in AI/ML, Data Science, Generative AI, or Cloud Technologies.
3–6 years of relevant experience in Machine Learning / AI application development.
Experience in developing or supporting enterprise/web-based applications.
Exposure to EdTech, LMS platforms, Digital Learning Ecosystems, or Online Education will be preferred.
Experience working with cross-functional stakeholders and external technology vendors/teams is desirable
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