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3 days ago

Chennai India Saint-Gobain Full time

Job Description Job Title: Data Scientist RAG & Edge AI Systems Location: Chennai Experience: 3+ years Joining: Immediate to 30 days preferred About the Role We are seeking a Data Scientist with strong experience in RAG (Retrieval-Augmented Generation), LLMs, and Edge AI processing to join our growing AI engineering team. This role combines hands-on engineering with strategic AI design Key Responsibilities - Design and develop LLM and RAG-based systems that enhance knowledge discovery, automation, and decision support. - Build and orchestrate end-to-end AI pipelines using Azure AI Studio, Logic Apps, and Data Factory. - Develop APIs and microservices for AI model integration with business and plant systems. - Optimize and deploy deep learning models to edge devices (e.g., NVIDIA Jetson, AI PCs) for real-time inference. - Fine-tune LLMs for domain-specific tasks, balancing accuracy, speed, and compute efficiency. - Collaborate cross-functionally with data engineers, software developers, and domain experts to bring AI prototypes to production. - Monitor model performance, automate retraining pipelines, and ensure compliance with data governance and security standards. Required Skills & Experience - RAG & LLMs: Experience building Retrieval-Augmented Generation systems using frameworks such as LangChain, LlamaIndex, or Azure OpenAI Service. - Azure Stack: Hands-on experience with Azure AI Studio, Azure Machine Learning, Logic Apps, Functions, and Data Factory. - Programming: Strong proficiency in Python, with experience in PyTorch, TensorFlow, LangChain, and FastAPI. Edge AI Processing: - Deploying and optimizing models on edge devices such as NVIDIA Jetson, Intel AI PCs, or ARM-based systems. - Proficiency in TensorRT for real-time inference. - Familiarity with Docker and remote monitoring for distributed edge workloads. - Data Handling: Experience with SQL and vector databases for retrieval and embedding management. - Visualization & Monitoring: Experience building dashboards using Power BI, Streamlit, or similar tools for inference metrics and explainability. Preferred / Nice-to-Have - Strong understanding of vector search optimization, document embeddings, and semantic retrieval at scale. - Experience with multimodal AI systems (text and image) for industrial or enterprise use. - Understanding of model compression, quantization, and GPU optimization for on-device AI. - Experience integrating AI models with manufacturing systems (MES, SCADA, or PLC data). - Familiarity with Elixir/Phoenix for chatbot or API integration within enterprise platforms. - Awareness of AI safety, ethical AI, and data privacy frameworks in regulated environments.

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