Data Scientist

Job Title: Data ScientistJob Type: Full-timeLocation: BengaluruNotice Period: 15 days or immediate joinerExperience: 0-2 Years

Job Summary

Data Scientist (LLM)

Machine Learning (ML), Deep Learning (DL), and Large Language Models (LLMs)

conversational AI/chatbots

LLM agent development frameworks

LangChain, LlamaIndex, AutoGen, and LangGraph

Key Responsibilities

• Develop, fine-tune, and deploy Large Language Models (LLMs) for various applications, including chatbots, virtual assistants, and enterprise AI solutions.
• Build and optimize conversational AI solutions with at least 1 year of experience in chatbot development.
• Implement and experiment with LLM agent development frameworks such as LangChain, LlamaIndex, AutoGen, and LangGraph.
• Design and develop ML/DL-based models to enhance natural language understanding capabilities.
• Work on retrieval-augmented generation (RAG) and vector databases (e.g., FAISS, Pinecone, Weaviate, ChromaDB) to enhance LLM-based applications.
• Optimize and fine-tune transformer-based models such as GPT, LLaMA, Falcon, Mistral, Claude, etc., for domain-specific tasks.
• Develop and implement prompt engineering techniques and fine-tuning strategies to improve LLM performance.
• Work on AI agents, multi-agent systems, and tool-use optimization for real-world business applications.
• Develop APIs and pipelines to integrate LLMs into enterprise applications.
• Research and stay up-to-date with the latest advancements in LLM architectures, frameworks, and AI trends.
  

Required Skills & Qualifications

• 0-2 years of experience in Machine Learning (ML), Deep Learning (DL), and NLP-based model development.
• Hands-on experience in developing and deploying conversational AI/chatbots is Plus
• Strong proficiency in Python and experience with ML/DL frameworks such as TensorFlow, PyTorch, and Hugging Face Transformers.
• Experience with LLM agent development frameworks like LangChain, LlamaIndex, AutoGen, LangGraph.
• Knowledge of vector databases (e.g., FAISS, Pinecone, Weaviate, ChromaDB) and embedding models.
• Understanding of Prompt Engineering and Fine-tuning LLMs.
• Familiarity with cloud services (AWS, GCP, Azure) for deploying LLMs at scale.
• Experience in working with APIs, Docker, FastAPI for model deployment.
• Strong analytical and problem-solving skills.
• Ability to work independently and collaboratively in a fast-paced environment.
  

Good To Have

• Experience with Multi-modal AI models (text-to-image, text-to-video, speech synthesis, etc.).
• Knowledge of Knowledge Graphs and Symbolic AI.
• Understanding of MLOps and LLMOps for deploying scalable AI solutions.
• Experience in automated evaluation of LLMs and bias mitigation techniques.
• Research experience or published work in LLMs, NLP, or Generative AI is a plus.