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Tier-1 brand, mid-level ML role, metro location and generalist LLM/cloud skills drive high competition.
ML/LLM model fine-tuning, RAG pipelines and cloud deployment require specialized ML backgrounds.
Explicit 3–5 years and specialized LLM, RAG, and cloud deployment requirements imply high shortlisting strictness.
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Design and implement Retrieval-Augmented Generation (RAG) pipelines for intelligent solutions.
Fine-tune and optimize Machine Learning/Large Language Models for domain-specific applications.
Develop, deploy, and scale AI solutions including prediction, automation, and classification use cases on cloud platforms (Azure/GCP), integrating models into scalable software tools and workflows.
Bachelor's degree in Engineering (BE, B.Tech).
3 to 5 years of work experience in AI/ML development.
Experience with fine-tuning ML/LLM models and feature engineering to ensure data quality.
Experience deploying and scaling AI solutions on cloud platforms such as Azure or GCP.
Experienced in end-to-end AI/ML pipeline development including data preprocessing and feature engineering.
Skilled in integrating advanced AI models into scalable software workflows in cloud environments.
Focused on domain-specific model customization and operational deployment of AI solutions.