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Mid-level, Bangalore location and common Data Scientist title increase competition despite LLM specialization.
Specialized LLM/NLP and model production skills limit cross-industry transfer, indicating high sensitivity.
Explicit 4-6 year requirement plus mandatory LLM fine-tuning, prompt engineering, and production skills raise strictness.
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Fine-tune and experiment with open source Large Language Models (LLMs) for applications like chatbots, question-answering, and recommendation engines.
Pre-process, clean, and manage large text datasets for LLM fine-tuning and evaluate model performance for improvement.
Collaborate with backend and DevOps teams to integrate and productionize LLM inference pipelines within a multi-tenant SaaS platform.
4-6 years of experience as a Data Scientist.
Proven experience with large text datasets and prompt engineering for NLP tasks.
Hands-on experience with deep learning frameworks such as TensorFlow or PyTorch.
Strong understanding of NLP techniques.
Experienced in applying advanced NLP and LLM architectures in production environments with SaaS platforms.
Operates effectively at the intersection of AI research, product development, and engineering integration.
Capable of contributing to LLM product requirements and using cloud platforms for deployment (AWS, GCP, Azure experience is a plus).