Posted:2 weeks ago|
Platform:
On-site
Full Time
Experience: 4-6 Years Key Responsibilities β Fine-tune and train open-source LLMs (e.g., LLaMA or similar) for downstream applications. β Build and orchestrate multi-agent workflows using LangGraph for production use cases. β Implement and optimize RAG pipelines, including embedding stores and retrievers. β Deploy and manage models via Hugging Face with robust inference capabilities. β Develop modular backend components and APIs using Python. β Ensure reproducibility, efficiency, and scalability in all LLM training and deployment tasks. β Independently build and deliver project components from the ground up. Must-Have Skills β 4β6 years of hands-on experience in AI/ML engineering roles. β Strong experience with LangGraph in real-world, multi-agent applications. β Production-level experience in LLM fine-tuning and deployment (not POCs or academic work). β Deep understanding of RAG pipeline design and implementation. β Proficiency in Python for data pipelines and model orchestration. β Familiarity with open-source LLMs like LLaMA, Mistral, Falcon, etc. β Deployment experience with the Hugging Face ecosystem. Show more Show less
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