Hyderabad, Telangana, India
Information Technology
Full-Time
PayMe
Overview
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 .
- 1-4 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.
- 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.
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