Location : Bangalore, India (On-site)
Department : AI / ML
Type : Internship (3–6 months, with extension or full-time conversion opportunity)
About Us
We're an AI / ML research-driven team focused on building intelligent AI Agents and RAG-based systems for real-world applications in finance, business, and personal assistance.
Our work combines applied research and fast-paced product development to create powerful, modular AI systems that think, reason, and act.
About the Role
As an AI / ML Intern, you'll work closely with our core AI / ML team on projects involving LLMs, retrieval systems, and agentic reasoning.
You'll contribute to experiments, data preparation, model evaluation, and prototype development, gaining exposure to both research concepts and production-level AI systems.
Responsibilities
- Assist in building and evaluating LLM- and agent-based pipelines (RAG, reasoning, tool use, etc.).
- Conduct small-scale experiments and contribute to prompt design and prompt evaluation.
- Help integrate LLMs with APIs, databases, and internal tools.
- Explore and document recent AI agent frameworks and LLM techniques.
- Collaborate with backend engineers to test and deploy prototypes.
Required Skills
Strong foundations in Machine Learning and Deep Learning concepts.Good understanding of LLM fundamentals - tokenization, embeddings, attention, context, etc.Some exposure to Prompt Engineering and reasoning patterns like Chain of Thought or ReAct.Experience in Python and libraries like PyTorch, NumPy, Pandas.Familiarity with Git / GitHub for version control.Curiosity and ability to learn quickly in a research-focused environment.Preferred Skills
Experience with Hugging Face Transformers / Datasets.Exposure to RAG systems and vector databases (Qdrant, Pinecone, Weaviate, Chroma).Awareness of LangChain, LangGraph, or other LLM / Agent frameworks.Knowledge of Docker, Redis, or basic database usage (PostgreSQL / MongoDB).Understanding of OpenAI, Anthropic, Ollama, or other model inference APIs.What We Value
Curiosity, ownership, clarity of thought, and an understanding of why systems work the way they do, not just how to use them.
Perks
Hands-on experience with real-world AI deployments.Work with state-of-the-art AI tools and platforms.Mentorship from top AI engineers and researchers.Flexible, innovation-driven work culture.Skills Required
Numpy, Github, Git, Machine Learning, Pandas, Pytorch, Python, Deep Learning