MULTIMODAL AI INTERN

About the program EduRankAI invites applications for the position of Multimodal AI Intern to join its Artificial Intelligence and Multimodal Research team. This fulltime internship is designed for students and recent graduates who are passionate about Multimodal Artificial Intelligence, Machine Learning, Deep Learning, Computer Vision, Natural Language Processing NLP, Speech Processing, Audio Intelligence, Video Understanding, and Foundation Models. As a Multimodal AI Intern, you will contribute to developing nextgeneration AI systems capable of understanding, reasoning, and generating information across multiple data modalities including text, images, audio, video, and structured information. These technologies play a critical role in powering AquinTutor's intelligent tutoring platform, enabling AIdriven visual explanations, voicebased learning, diagram interpretation, multimodal question answering, interactive educational content, and personalized learning experiences across the EduRankAI ecosystem. As a Multimodal AI Intern, you will collaborate with AI researchers, machine learning engineers, computer vision specialists, NLP engineers, software developers, and product teams to build, evaluate, and optimize multimodal AI solutions. Your responsibilities will include researching stateoftheart multimodal architectures supporting experiments involving text, image, audio, and video understanding preparing, preprocessing, and annotating multimodal datasets developing evaluation benchmarks for multimodal reasoning and generation tasks assisting in training, finetuning, and evaluating multimodal foundation models implementing multimodal embedding and feature fusion techniques analysing model performance, robustness, and limitations supporting RetrievalAugmented Generation RAG workflows involving multimodal content documenting research methodologies, experiments, and findings contributing to prototype development for educational AI applications and collaborating with multidisciplinary teams to integrate multimodal AI capabilities into productionready tutoring systems. Applicants should possess a strong understanding of Python programming, Artificial Intelligence, Machine Learning, Deep Learning, software engineering principles, linear algebra, probability, and statistics. Familiarity with PyTorch, TensorFlow, Hugging Face Transformers, OpenCV, NumPy, Pandas, Jupyter Notebooks, Git, Computer Vision, Natural Language Processing NLP, Speech Processing, Audio Analysis, Multimodal Foundation Models, CLIP, BLIP, LLaVA, Whisper, Vision Transformers ViTs, image preprocessing, audio preprocessing, video processing, embeddings, vector databases, GPU computing, or cloudbased AI development environments will be considered an advantage but is not mandatory. Knowledge of Generative AI, Large Language Models LLMs, RetrievalAugmented Generation RAG, multimodal reasoning, diffusion models, AI evaluation methodologies, or model optimization techniques will also be beneficial. Candidates with academic projects, hackathons, research work, AI competitions, opensource contributions, or personal projects involving Computer Vision, NLP, speech recognition, multimodal AI, or Generative AI are strongly encouraged to apply. Throughout the internship, participants will receive structured mentorship, continuous technical guidance, engineering best practices, research discussions, architecture reviews, code reviews, and exposure to modern Multimodal AI development workflows. Interns will gain practical experience in multimodal model development, multimodal data processing, AI evaluation, foundation model experimentation, technical documentation, collaborative engineering, AI research methodologies, and productiongrade Artificial Intelligence systems while contributing directly to live AI initiatives and educational technology innovations. We are looking for individuals with exceptional analytical ability, logical reasoning, mathematical aptitude, creativity, scientific curiosity, problemsolving skills, attention to detail, communication skills, ownership, adaptability, teamwork, engineering discipline, research orientation, and a continuous learning mindset. The internship is primarily conducted onsite at the EduRankAI campus with structured mentorship and collaborative engineering activities. Remote participation may be permitted only in exceptional, preapproved cases. Applications submitted under EduRankAI's Talent Accessibility Initiative are completely free. This is an unpaid internship intended to provide meaningful industry exposure, structured mentorship, handson Multimodal AI experience, professional portfolio development, and opportunities for outstanding performers to be considered for advanced AI research projects, internship extensions, preplacement interviews, research collaborations, or future fulltime opportunities based on performance and organizational requirements. Perks Certificate of Completion Letter of Recommendation for exceptional performers Mentorship from Senior AI Researchers and Multimodal AI Engineers Hands-on experience with production-grade Multimodal AI and Foundation Models Exposure to Computer Vision, NLP, Speech AI, and Vision-Language Models Opportunity to contribute to live AI Tutor, multimodal educational technologies, and AI research initiatives Professional Multimodal AI portfolio development Cross-functional collaboration with AI research, software engineering, product development, and education teams Performance-based Pre-Placement Interview opportunity Exposure to cutting-edge Multimodal AI, Generative AI, Large Language Models, and next-generation intelligent systems 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 This is a full-time internship requiring a commitment of six days per week, for a duration of three months. The internship is primarily conducted on-site at the EduRankAI campus with structured mentorship and collaborative engineering activities. Remote participation may be permitted only in exceptional cases with prior organizational approval. Interns will contribute to live Multimodal AI and Artificial Intelligence projects while maintaining professionalism, confidentiality, documentation standards, engineering best practices, research integrity, responsible AI principles, and project timelines. Participants will collaborate with multidisciplinary teams, conduct multimodal AI experiments, develop intelligent AI solutions, evaluate model performance, prepare technical documentation, participate in engineering and research reviews, and support continuous improvements in production-ready multimodal systems. Successful completion of the internship will be evaluated based on technical competency, research contribution, engineering quality, documentation standards, collaboration, innovation, ownership, consistency, professionalism, and overall contribution throughout the internship. Number of openings 10