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Large Language Model Specialist

1 week ago


India Steps AI Full time

As a key member of our dynamic team, you will contribute to the development and deployment of advanced AI solutions in real-world applications.

The ideal candidate will have a deep understanding of transformer architectures, strong foundation of LLM techniques and models, and strong MLOps foundations.

Responsibilities:
  1. Design and develop multi-agent systems for enterprise use cases.
  2. Deploy scalable MLOps pipelines and optimize LLM performance in production.
  3. Work with advanced models (LLaMA, GPT, etc.) and optimize them for cloud deployment.
  4. Design and implement efficient RAG systems (Graph, Struct, Naive) for enhanced retrieval.
  5. Refine prompts using techniques like CoT, ToT, and GoT to improve LLM accuracy.
  6. Develop LLM-based agents for dynamic tasks using orchestration frameworks.
  7. Prototype and Develop Production-level pipelines for advanced LLM orchestration and RAG.
Requirements:
  1. Strong understanding of Machine Learning (ML), Deep Learning (DL), and Natural Language Processing (NLP) with hands-on experience in Large Language Models (LLMs).
  2. In-depth knowledge of transformer architectures, including BERT, GPT, T5, and state-of-the-art models such as GPT-4, Mistral, or LLaMA.
  3. Proficiency in building and deploying RAG pipelines, with practical knowledge of Graph RAG, Agentic RAG, and Naive RAG methodologies.
  4. Ability to design, deploy, and maintain production-level RAG pipelines with optimized retrieval, ranking, and generative model interactions.
  5. Understanding of pseudo-code and RAG systems.
  6. Experience in designing, deploying, and orchestrating multi-agent systems using LLM-based agents.
  7. Familiarity with tool-calling frameworks, LLM-sandboxing, and LLMs' interaction with external systems.
  8. Strong foundation in MLOps practices for deploying scalable, production-ready AI models.
  9. Experience with advanced prompting techniques.
  10. Proficiency with popular frameworks like PyTorch, TensorFlow, and LangChain.
  11. Excellent communication skills and collaboration abilities.
Benefits:
  1. Cutting-edge opportunity to work with the latest technologies.
  2. Mentorship from experienced AI engineers.
  3. Flexible and dynamic work environment.