AI / ML Product Engineer Intern (NLP, LLM, Product) — AVK Tech · Hyderabad
About this role
AI / ML Product Engineer Internship at AVK Tech in Hyderabad — develop and deploy AI / ML-based products, NLP and LLM applications alongside the engineering team. Great for freshers who want production AI-product skills, not just model notebooks. Hybrid, flexible timing.
About this internship at AVK Tech. AI / ML Product Engineer Internship at AVK Tech in Hyderabad — develop and deploy AI / ML-based products, NLP and LLM applications alongside the engineering team. Great for freshers who want production AI-product skills, not just model notebooks. Hybrid, flexible timing. This listing on cloudsoftsol.com is curated for students and freshers in India who are actively looking for AI / ML, Data Science and software internships in Hyderabad. The role is an internship, hybrid, and is open to final-year students and recent graduates — initiative and a real project portfolio matter more than years of experience. Read the responsibilities and requirements below carefully and tailor your application to the specifics; a single, well-explained project beats a long list of course names. Cloud Soft Solutions runs the leading AI, Data Science, Python, AWS, Azure, GCP and DevOps training and placement programmes in Hyderabad and Bangalore — if you would like coaching for AI / ML internships and fresher roles, mock interviews, resume review or portfolio help, please contact us at info@cloudsoftsol.com. We do not charge candidates a fee for placement assistance; companies sponsor our involvement.
Responsibilities
Assist in AI product development end to end — model integration, building data-driven features, and deploying ML into a real product rather than stopping at a trained model. Work on NLP and LLM projects: prompt design, retrieval, evaluation, and wiring language models into product features that users actually interact with. Collaborate on full-stack AI solutions with the engineering team — understanding how the model, the API, and the frontend fit together. Test and optimise ML models for real applications — latency, cost, and quality trade-offs in production, not just offline accuracy. Contribute to documentation and iterate quickly on feedback in a product-focused environment.
Requirements
Pursuing a degree in Computer Science, Data Science or a related field; freshers are encouraged. Working Python and familiarity with basic ML frameworks. Interest in NLP / LLMs and in how AI becomes a shipped product (APIs, integration, deployment) rather than only model training. Curiosity, ownership, and the ability to learn quickly in a hands-on setting. Any personal AI projects — chatbots, RAG apps, fine-tunes, small deployed demos — strengthen the application significantly.