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Tier-1 brand, Bangalore location, and desirable ML/LLM skillset make candidate competition high.
Core ML, DL, and LLM skills are broadly transferable across industries, with moderate healthcare domain bias.
Mandatory 7+ years and specific ML/LLM, DL framework, and production deployment requirements raise shortlisting strictness.
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Design, develop, and deploy AI-powered solutions using no-code, low-code, and advanced platforms to improve products, workflows, and decision-making.
Lead end-to-end Machine Learning (ML) and Deep Learning (DL) initiatives, including problem definition through production deployment.
Implement scalable ML models, specifically with expertise in Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) architectures.
7+ years of experience leading end-to-end ML and DL projects with production deployment.
Hands-on expertise with deep learning frameworks like TensorFlow and PyTorch and proficiency in Python (Pandas, NumPy, Scikit-learn).
Practical experience working with Large Language Models (LLMs) and familiarity with Retrieval-Augmented Generation (RAG) architectures.
Work Experience Required: 7+ years as explicitly mentioned; Notice period: Not explicitly mentioned.
Experienced in deploying scalable AI/ML models in production environments with cross-functional collaboration skills.
Strong background in NLP and conversational AI via LLMs, including advanced knowledge of RAG architectures and AI agent-based systems.
Comfortable working with data preprocessing, feature engineering, model evaluation, and potentially cloud platforms (AWS, GCP, Azure).