EDGE AI INTERN

About the program EduRankAI invites applications for the position of Edge AI Intern to join its Artificial Intelligence and Embedded Systems Engineering team. This fulltime internship is designed for students and recent graduates who are passionate about Edge Artificial Intelligence, Embedded Systems, Machine Learning, Computer Vision, Internet of Things IoT, TinyML, AI Optimization, and intelligent computing on resourceconstrained devices. As an Edge AI Intern, you will contribute to optimizing, deploying, and evaluating Artificial Intelligence models that run efficiently on edge devices, enabling realtime intelligence while minimizing latency, power consumption, memory usage, and cloud dependency across EduRankAI's AIpowered educational products and research initiatives. As an Edge AI Intern, you will collaborate with AI researchers, machine learning engineers, embedded systems engineers, software developers, and platform teams to develop efficient AI solutions for edge computing environments. Your responsibilities will include optimizing machine learning and deep learning models for edge deployment through quantization, pruning, and model compression techniques benchmarking model performance on resourceconstrained hardware evaluating latency, accuracy, memory consumption, and energy efficiency supporting deployment using TensorFlow Lite, ONNX Runtime, TensorFlow Lite Micro, or similar edge AI frameworks assisting with AI inference on embedded devices conducting performance profiling and optimization integrating AI models with embedded hardware platforms documenting optimization tradeoffs preparing benchmarking reports supporting firmware and software integration maintaining reproducible deployment workflows and collaborating with multidisciplinary teams to improve productionready Edge AI solutions. Applicants should possess a strong understanding of Python programming, machine learning, deep learning fundamentals, embedded systems concepts, computer architecture, operating systems, and software engineering principles. Familiarity with TensorFlow Lite, TensorFlow Lite Micro, ONNX Runtime, OpenCV, PyTorch, TensorFlow, CUDA basics, Raspberry Pi, NVIDIA Jetson, Arduino, ESP32, ARMbased platforms, Linux, CC++, Git, Docker, model quantization, pruning, optimization techniques, computer vision, TinyML, or IoT development will be considered an advantage but is not mandatory. Knowledge of Computer Vision, Natural Language Processing NLP, edge deployment, hardware acceleration, AI inference optimization, or embedded Linux will also be beneficial. Candidates with academic projects, hackathons, research work, robotics competitions, opensource contributions, or personal projects involving embedded AI, robotics, IoT, or Edge AI are strongly encouraged to apply. Throughout the internship, participants will receive structured mentorship, continuous technical guidance, engineering best practices, code reviews, and exposure to modern Edge AI development workflows. Interns will gain practical experience in model optimization, AI deployment, embedded AI systems, hardware benchmarking, performance analysis, technical documentation, collaborative engineering, AI inference optimization, and productionready Edge AI applications while contributing directly to live Artificial Intelligence and embedded systems projects. We are looking for individuals with strong analytical ability, mathematical aptitude, logical reasoning, curiosity, creativity, engineering discipline, problemsolving skills, attention to detail, communication skills, ownership, teamwork, adaptability, 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 Edge 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 Embedded Systems Engineers Hands-on experience with production-grade Edge AI and embedded AI systems Exposure to model optimization, quantization, TinyML, and AI deployment Opportunity to contribute to live Edge AI research and intelligent embedded products Professional Edge AI portfolio development Cross-functional collaboration with AI research, embedded systems, software engineering, and platform teams Performance-based Pre-Placement Interview opportunity Exposure to modern Edge AI, TinyML, embedded computing, and intelligent hardware technologies Who can apply? Only those candidates can apply who: are from Any and specialisation from 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 Edge AI and embedded systems projects while maintaining professionalism, confidentiality, documentation standards, engineering best practices, research integrity, and project timelines. Participants will collaborate with multidisciplinary teams, optimize AI models for deployment, benchmark embedded hardware, prepare technical documentation, participate in engineering reviews, and support continuous improvements in production-ready Edge AI solutions. Successful completion of the internship will be evaluated based on technical competency, optimization quality, analytical ability, engineering standards, documentation quality, collaboration, innovation, ownership, consistency, professionalism, and overall contribution throughout the internship. Number of openings 10