AI / ML Intern, LLM Applications
Altumind
This job at a glance
- Who can apply
- Freshers and up to 1 year · B.Tech / B.E., M.Tech, MCA or M.Sc
- Must know
- REST APIsPython
- Nice to have
- Machine learningLLMsPyTorchNLP
- Work
- On-site in Hyderabad · internship
- Pay
- Not stated by the employer.
- Skill demand
- Machine learning84%Python74%LLMs72%REST APIs49%of 99 similar fresher jobs posted in India this week
- Listed
- 10 Nov 2026 · still open
Sign in free to see which of these skills your resume already shows.
About the Role
AI / ML Intern - LLM Applications at Altumind, focusing on the AI layer of education products, including systems for assessment generation, learner response evaluation, and learning analytics. This role involves working on practical LLM applications and contributing to features moving into real product use.
Key Responsibilities
- Build LLM features covering prompt design, API integration, structured outputs, and product integration.
- Design and iterate prompts to produce reliable and consistent outputs.
- Build retrieval pipelines using chunking, embeddings, and vector search.
- Create test sets and evaluate AI outputs for quality, accuracy, and consistency.
- Compare prompts and models to identify effective approaches.
- Investigate AI output failures across prompts, models, retrieved context, and response parsing.
- Document findings and contribute to improving AI feature performance.
Requirements & Tech Stack
- Good Python programming skills.
- Working understanding of core Generative AI and Machine Learning concepts.
- Hands-on experience with OpenAI, Claude, or other LLM APIs.
- Exposure to RAG, embeddings, or vector databases.
- Experience writing prompts for structured and repeatable outputs.
- Strong attention to detail when evaluating AI-generated responses.
- Ability to learn quickly and work through unfamiliar technical problems.
Preferred Skills
- Experience building an end-to-end LLM application.
- Experience with evaluation datasets or automated evaluation pipelines.
- Familiarity with Hugging Face, PyTorch, or Transformers.
- Understanding of token usage, model pricing, and cost optimization.
- Previous AI, ML, or NLP projects, including academic or personal projects.
Qualifications
Students or recent graduates pursuing B.E./B.Tech, M.E./M.Tech, MCA, M.Sc., or a related degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related field.
Ideal Candidate Profile
A hands-on learner who enjoys experimenting with LLMs, testing different approaches, and understanding why an AI system succeeds or fails. Comfortable turning ideas into working prototypes and paying close attention to the quality of AI-generated outputs.