GenAI Intern

Selected intern's day-to-day responsibilities include:

• Develop LLM applications using Retrieval-Augmented Generation (RAG) pipelines for accurate, context-aware outputs.
• Fine-tune open-source LLMs using PEFT/LoRA/QLoRA. Perform post-training using different methods, including RL and DPO.
• Validate and test custom LLM-based applications and/or fine-tuned models.
• Design and optimize semantic search systems using embeddings, vector databases, and ranking models.
• Analyze datasets, identify gaps in quality and coverage, and improve them systematically.
• Design experiments (A/B testing, offline evaluation) to validate system performance.
• Collaborate with AI engineers and domain experts to integrate systems into real-world applications.
• Create and maintain technical documentation.

Who you are

• Someone with a strong technical background and an interest in LLMs and machine learning, specifically NLP.
• Proficiency in Python (experience with ML frameworks is a plus).
• Understanding of LLMs, embeddings, vector search, RAG architectures, and different post-training methods.
• Familiarity with search systems and ranking algorithms.
• Knowledge of Deep Reinforcement Learning, DPO, RLHF and RLVR would be plus
• Having higher qualifications, such as an MTech or a higher degree, is a plus.