AI Intern

All rolesIAI InternInfoCare · Remote · Posted yesterdayInternship · Remote1 opening60-minute screening test, right after you applySign in to applySaveAbout the jobAI Intern: Machine Learning, GenAI & AI Agents Location: Kathmandu, Nepal Employment Type: Internship Experience: Entry-level / Freshers About the Role We are looking for a motivated AI Intern interested in building and experimenting with modern AI systems. You will work across Machine Learning, Deep Learning, Generative AI, AI Agents, model evaluation, and AI security, gaining hands-on experience with real-world AI applications. Key Responsibilities Develop and experiment with Machine Learning and Deep Learning models. Work with LLMs, embeddings, RAG, multimodal AI, and Generative AI applications. Build AI agents and agentic workflows using frameworks such as LangGraph, LangChain, or similar tools. Implement tool calling, workflow orchestration, memory, and multi-agent systems. Design and run LLM/AI evaluations covering accuracy, relevance, groundedness, latency, robustness, and reliability. Create evaluation datasets, benchmarks, and automated evaluation pipelines. Explore AI security and safety, including prompt injection, jailbreaks, data leakage, insecure tool usage, and adversarial inputs. Perform experimentation, debugging, error analysis, and performance optimization. Work with APIs, vector databases, model-serving infrastructure, and AI development tools. Document experiments, findings, and technical implementations. Requirements Pursuing or recently completed a degree in Computer Science, AI/ML, Electronics, Software Engineering, or a related field. Strong understanding of Python and basic software development practices. Understanding of fundamental Machine Learning and Deep Learning concepts. Familiarity with PyTorch, TensorFlow, or similar frameworks. Basic understanding of LLMs, Transformers, embeddings, and RAG. Interest in AI agents, function/tool calling, and agentic systems. Basic understanding of model evaluation and experimentation. Strong problem-solving and analytical skills. Willingness to learn new AI frameworks, models, and technologies quickly. Good to Have Experience with LangChain, LangGraph, LlamaIndex, CrewAI, or OpenAI/Gemini APIs. Experience building RAG or AI-agent applications. Familiarity with vector databases such as pgvector, Pinecone, Qdrant, or Chroma. Knowledge of LLM evaluation frameworks such as Ragas, DeepEval, or similar. Understanding of AI security, red teaming, prompt injection, jailbreaks, or guardrails. Experience with Git, Docker, REST APIs, FastAPI, or cloud platforms. Familiarity with MLOps, model serving, observability, or experiment tracking. What You Will Learn End-to-end development of modern AI/ML systems. Building production-oriented GenAI and agentic applications. LLM evaluation and benchmarking. AI security, red teaming, and safety techniques. RAG, multimodal AI, tool use, and agent orchestration. Practical model deployment, monitoring, and optimization. Who Should Apply This internship is suitable for someone who enjoys building, experimenting, breaking things, evaluating models, and learning how modern AI systems work. Strong fundamentals and curiosity are more important than knowing every framework.