Codemythos solutions

Job Summary: We are seeking an innovative and highly skilled Data Scientist (LLM & Generative AI) with 5+ years of experience in machine learning, natural language processing, and applied AI. The ideal candidate will have deep expertise in large language models (LLMs), prompt engineering, retrieval-augmented generation (RAG), and agentic AI approaches. This role involves developing intelligent, autonomous, and scalable AI solutions that leverage cutting-edge research in generative AI, transformers, and multi-agent systems. In addition, the candidate will be expected to collaborate closely with engineering teams to bring research into production. Key Responsibilities: Research, design, and implement advanced LLM-based solutions for NLP, knowledge retrieval, and reasoning tasks. Develop and fine-tune LLMs (e.g., GPT, LLaMA, Falcon, Claude) for domain-specific use cases. Apply agentic AI approaches (multi-agent systems, autonomous agents, decision-making pipelines) to real-world business challenges. Design and implement retrieval-augmented generation (RAG) pipelines to combine structured/unstructured data with LLM capabilities. Build and optimize prompt engineering frameworks, evaluation metrics, and automated testing for generative AI outputs. Collaborate with ML engineers to deploy models into scalable cloud environments (AWS/GCP/Azure). Work with cross-functional teams to integrate LLM-powered agents into applications, workflows, and customer-facing products. Stay up-to-date with the latest research in LLMs, generative AI, reinforcement learning, and agentic architectures. Mentor junior team members and contribute to building an internal knowledge base on applied AI best practices. Requirements: Must-Have Skills: 5+ years of experience in data science, ML, or AI research with a focus on NLP and deep learning. Strong experience working with transformer architectures (e.g., BERT, GPT, T5, LLaMA). Hands-on expertise in fine-tuning and deploying LLMs using frameworks like Hugging Face Transformers, LangChain, or Haystack. Deep understanding of agentic AI approaches, including orchestration, multi-agent workflows, and autonomous reasoning systems. Proficiency in Python and ML libraries (PyTorch, TensorFlow, Hugging Face, LangChain, Ray). Strong background in applied NLP techniques such as text classification, summarization, embeddings, semantic search, and dialogue systems. Experience building RAG pipelines with vector databases (e.g., Pinecone, Weaviate, FAISS, Milvus). Familiarity with MLOps and cloud deployment (AWS Sagemaker, GCP Vertex AI, Azure ML). Nice-to-Have Skills: Knowledge of reinforcement learning (RLHF, RLAIF) for LLM optimization. Experience with multi-modal models (text, image, speech). Familiarity with graph databases and knowledge graphs for reasoning tasks. Contributions to open-source projects in NLP/LLM space. Understanding of privacy, security, and ethical considerations in generative AI. Location- remote Salary -25lpa Experience -5+years 6 months contract (extendable) Show more Show less