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Tier-1 brand, metro locations, mid-level ML generalist role with broad GenAI requirements increases competition.
Specialized ML/LLM skills limit non-ML applicants, but are transferable across industries.
Explicit 6–8 years plus many mandatory ML/LLM technical skills enforces strict shortlisting filters.
Design, develop, deploy, and monitor AI/GenAI and Retrieval-Augmented Generation (RAG) solutions in production environments.
Fine-tune, evaluate Large Language Models (LLMs), and develop prompt engineering strategies.
Collaborate cross-functionally to deliver AI-driven features and contribute to AI system architecture design.
6–8 years of relevant work experience in AI/ML and Generative AI.
Advanced proficiency in Python, machine learning (supervised/unsupervised, NLP), and generative AI techniques including RAG and vector search.
Experience with tools such as LangChain/LlamaIndex, PyTorch/TensorFlow, HuggingFace, vector databases, and cloud platforms (AWS/Azure/GCP).
Work Experience Required: 6–8 years
Strong expertise in productionizing AI and ML pipelines including model monitoring and MLOps practices.
Familiar with large-scale GenAI solutions, multi-agent frameworks, and fine-tuning methods such as LoRA, PEFT, and QLoRA.
Experienced in working collaboratively with engineering, product teams, and subject matter experts to implement scalable AI solutions in business settings.