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Mid-level ML/AI role, popular title, metro locations, and broad skill requirements drive high competition.
Role demands specialized LLM, RAG, vector DB and MLOps expertise, making cross-industry transfer difficult.
Mandatory LLM, MLOps, cloud skills and explicit experience range enforce high shortlisting strictness.
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Design, develop, test, and deploy AI/ML and Generative AI solutions including LLM-based enterprise applications and Retrieval-Augmented Generation systems.
Build and optimize scalable data pipelines and APIs to support AI model training, inference, and deployment with MLOps practices such as monitoring and lifecycle management.
Collaborate with cross-functional teams to translate business requirements into AI solutions and implement model evaluation, fine-tuning, and performance monitoring.
4-10+ years of experience in AI/ML engineering, Generative AI, or Data Science.
Proficiency in Python and SQL programming languages.
Experience with Large Language Models (OpenAI, Anthropic, Llama) and associated technologies like prompt engineering, vector databases, semantic search, and retrieval-augmented generation.
Experience with at least one cloud platform (Azure, AWS, or GCP) and knowledge of REST APIs, Git, and software development best practices.
Deep experience specifically in Generative AI and LLM-based applications integrating advanced techniques such as Agentic AI and RAG solutions.
Hands-on expertise in MLOps practices covering model deployment, monitoring, versioning, and lifecycle management in cloud environments.
Ability to work cross-functionally translating complex AI concepts into scalable, production-ready solutions aligned with business goals.