Paymeindia - Data Scientist - GenAI/LLM

2 weeks ago

Noida, Uttar Pradesh, India PayMe Full time US$ 80,000 - US$ 1,50,000 per year

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 & Qualification

  • 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.

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.

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