About Us
We are
SVKM’s NMIMS Centre for Distance and Education (NCDOE) -
India’s Premier Institution for with core focus on
Distance & learning
. Visit us at for more information.
The ML Engineer will support the Centre for Distance & 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
K
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 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.
Requirements- Skills & Competencies
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.
Requirements- Education & work experience
- 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 Education will be preferred.
- Experience working with cross-functional stakeholders and external technology vendors/teams is desirable
