SEARCH INTELLIGENCE & DISCOVERY ENGINEERING INTERN

About the program EduRankAI is an Artificial Intelligence, Education Technology, Research, and Enterprise Technology organization developing intelligent digital platforms, enterprise software, and technology solutions for academia, industry, government, and global organizations. The Search Intelligence Discovery Engineering Internship provides practical exposure to search engines, information retrieval, semantic search, ranking systems, recommendation technologies, knowledge discovery, indexing, query processing, and AIpowered search platforms. Interns will contribute to the development of intelligent search and discovery systems that enable users to efficiently retrieve, rank, and discover relevant information across largescale digital platforms. Working alongside artificial intelligence, machine learning, software engineering, data science, and research teams, interns will gain handson experience in designing, developing, evaluating, and optimizing modern search systems, retrieval pipelines, recommendation algorithms, intelligent ranking models, and personalized discovery platforms while strengthening their understanding of technologies that power websites, enterprise search, digital libraries, ecommerce platforms, video platforms, social media, and largescale knowledge systems. Key Responsibilities Assist in developing intelligent search and discovery systems. Support document indexing, metadata management, and search data pipelines. Develop and evaluate keywordbased and semantic search solutions. Assist in implementing information retrieval and ranking algorithms. Support vector search and embeddingbased retrieval systems. Participate in recommendation and personalized content discovery projects. Assist in optimizing search relevance, ranking quality, and retrieval performance. Support search analytics, query analysis, and user behavior analysis. Evaluate search quality using standard information retrieval metrics. Prepare technical documentation, datasets, and engineering reports. Collaborate with AI, software engineering, data science, and research teams on live projects. Stay updated with advancements in search technologies, retrieval systems, and discovery platforms. Perform additional search engineering assignments as required. Learning Outcomes Interns will gain practical exposure to: Search Engine Architecture Information Retrieval Search Intelligence Semantic Search Vector Search Embedding Models Search Indexing Query Processing Ranking Algorithms Learning to Rank Recommendation Systems Personalized Discovery Knowledge Graphs Search Analytics Search Evaluation RetrievalAugmented Generation RAG Technical Documentation Eligibility Students pursuing or having completed: B.E.B.Tech in Computer Science Engineering Artificial Intelligence Machine Learning Data Science Information Technology Software Engineering Electronics Communication Engineering M.E.M.Tech in relevant disciplines MCA M.Sc. in Computer Science, Artificial Intelligence, Data Science, Mathematics, Statistics, Information Science, or related disciplines Any equivalent programme Strong programming skills, analytical thinking, mathematics, problemsolving abilities, and an interest in Artificial Intelligence, Search Technologies, and Information Retrieval will be an added advantage but are not mandatory. Department Artificial Intelligence Data Science Qualification Type UG PG Qualification B.E. B.Tech M.E. M.Tech MCA M.Sc. Select Specialisation Computer Science Engineering Artificial Intelligence Machine Learning Data Science Software Engineering Information Technology Information Science Mathematics Statistics Electronics Communication Engineering Any Relevant Engineering or Science Discipline Perks Internship Certificate Letter of Recommendation (Performance Based) Mentorship from experienced AI and engineering professionals. Opportunity to contribute to live search, retrieval, recommendation, and discovery platform projects. Exposure to modern search technologies, semantic search, information retrieval, ranking systems, recommendation engines, and AI-powered discovery platforms. Professional development sessions on Artificial Intelligence, Information Retrieval, software engineering, research methodologies, and scalable search architectures. Outstanding performers may be considered for extended internships, leadership opportunities, or future full-time positions based on organizational requirements. Who can apply? Only those candidates can apply who: are from Any and specialisation from Any are available for duration of 3 Months have relevant skills and interests Terms of Engagement Internship Type: Full-Time Mode of Internship: Online Duration: 3 Months Working Days: 6 Days per Week Total Engagement: Approximately 40 Hours Per Week (?480 Hours over 12 weeks) Project Work / Departmental Responsibilities: Approximately 5 Hours Per Day Holistic Well-being & Personal Development: Approximately 1 Hour 40 Minutes (1.67 Hours) Per Day, including physical fitness, mindfulness, reading, reflective learning, leadership development, community engagement, and other approved personal development activities. Weekly mentor reviews and performance evaluations will be conducted. Interns are expected to maintain professionalism, confidentiality, ethical conduct, and adherence to organizational policies. This is an unpaid internship. Internship Certificate will be awarded upon successful completion of internship requirements. Internship does not constitute an offer of employment. Number of openings 10