LLM ENGINEER INTERN

About the program EduRankAI invites applications for the position of LLM Engineer Intern to join its Large Language Model Engineering and AI Platform team. This fulltime internship is designed for students and recent graduates who are passionate about Large Language Models LLMs, Generative AI, AI Engineering, AI Infrastructure, Prompt Engineering, AI Agents, Model Deployment, and productiongrade Artificial Intelligence systems. Unlike researchfocused AI roles, this internship emphasizes the engineering, optimization, deployment, integration, scalability, and reliability of Large Language Models powering EduRankAI's AI Tutor, intelligent educational assistants, content generation platforms, research tools, and enterprise AI applications. As an LLM Engineer Intern, you will collaborate with AI engineers, platform engineers, software developers, DevOps engineers, and product teams to build scalable, secure, and reliable LLMpowered applications. Your responsibilities will include developing and maintaining LLM inference pipelines integrating commercial and opensource Large Language Models through APIs and selfhosted deployments implementing RetrievalAugmented Generation RAG pipelines optimizing inference latency, throughput, and infrastructure costs supporting prompt engineering and structured output workflows integrating vector databases and embedding models implementing caching strategies and request routing mechanisms monitoring model performance and reliability debugging production inference issues supporting API development and backend integration conducting load testing and performance benchmarking documenting deployment workflows, operational procedures, and engineering best practices and collaborating with multidisciplinary teams to build productionready AI systems that meet reliability, scalability, and security standards. Applicants should possess a strong understanding of Python programming, software engineering principles, REST APIs, data structures, algorithms, Linux, networking fundamentals, and Artificial Intelligence concepts. Familiarity with Large Language Models LLMs, OpenAIcompatible APIs, Hugging Face Transformers, LangChain, LlamaIndex, vLLM, Ollama, TensorRTLLM, FastAPI, Docker, Kubernetes, Git, RetrievalAugmented Generation RAG, embeddings, vector databases such as Pinecone, FAISS, ChromaDB, Milvus, or Weaviate, cloud platforms including AWS, Microsoft Azure, or Google Cloud Platform GCP, inference optimization techniques, GPU computing, caching strategies, API gateways, CICD pipelines, monitoring tools, or distributed systems will be considered an advantage but is not mandatory. Knowledge of AI Agents, function calling, structured outputs, model quantization, prompt engineering, observability, or production AI infrastructure will also be beneficial. Candidates with academic projects, hackathons, opensource contributions, research experience, AI competitions, or personal projects involving LLM applications, AI assistants, chatbot development, or AI infrastructure are strongly encouraged to apply. Throughout the internship, participants will receive structured mentorship, continuous technical guidance, engineering best practices, architecture reviews, code reviews, and exposure to modern LLM engineering workflows used in production environments. Interns will gain practical experience in Large Language Model deployment, AI infrastructure, inference optimization, RetrievalAugmented Generation RAG, API integration, AI observability, prompt engineering, technical documentation, collaborative software development, and production AI engineering while contributing directly to live Artificial Intelligence initiatives. We are looking for individuals with strong analytical ability, logical reasoning, engineering discipline, problemsolving skills, curiosity, attention to detail, communication skills, adaptability, ownership, teamwork, continuous learning ability, and a passion for building scalable Artificial Intelligence systems. 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 LLM Engineering experience, professional portfolio development, and opportunities for outstanding performers to be considered for advanced AI engineering 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 LLM Engineers and AI Platform Engineers Hands-on experience with production-grade Large Language Model infrastructure Exposure to Retrieval-Augmented Generation (RAG), AI APIs, inference optimization, and scalable AI systems Opportunity to contribute to live AI Tutor, enterprise AI applications, and LLM-powered products Professional LLM Engineering portfolio development Cross-functional collaboration with AI research, platform engineering, DevOps, software engineering, and product teams Performance-based Pre-Placement Interview opportunity Exposure to cutting-edge Generative AI, LLM deployment, AI infrastructure, and production engineering practices 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 LLM Engineering and Artificial Intelligence platform projects while maintaining professionalism, confidentiality, documentation standards, engineering best practices, operational discipline, responsible AI principles, and project timelines. Participants will collaborate with multidisciplinary teams, develop and optimize LLM inference pipelines, integrate AI services into production systems, monitor model performance, prepare technical documentation, participate in engineering reviews, and support continuous improvements in scalable AI infrastructure. Successful completion of the internship will be evaluated based on technical competency, engineering quality, analytical ability, documentation standards, collaboration, ownership, consistency, professionalism, and overall contribution throughout the internship. Number of openings 10