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Popular mid-level GenAI ML role with broad skillset demands, increasing competition despite a non-Tier1 employer.
Specialized ML/GenAI engineering and cloud MLOps requirements limit transferability across industries.
Explicit 2–5 years requirement plus mandatory ML/GenAI, cloud, RAG, and MLOps stack increases filtering strictness.
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Design, build, and deploy AI/ML models including Generative AI solutions and Retrieval-Augmented Generation (RAG) pipelines.
Develop and implement Agentic AI workflows for automation and multi-step task execution using Azure AI or similar cloud platforms.
Optimize scalable, production-ready AI/ML systems focusing on performance and cost efficiency in cloud and edge environments.
2–5 years of experience in AI/ML development.
Bachelor’s or Master’s degree in Computer Science, AI/ML, Data Science, or related field (B.E./B.Tech/M.Tech).
Strong programming skills in Python with experience in NumPy, Pandas, PyTorch/TensorFlow, LangChain, and Transformers.
Hands-on experience with Azure AI services or AWS/GCP AI platforms, including ML pipeline optimization and deployment tooling such as MLflow, Docker, and Kubernetes.
Experienced AI/ML developer proficient in Generative AI techniques including LLMs, embeddings, and prompt engineering.
Skilled in building complex AI systems integrating vector databases, knowledge graphs, and agentic frameworks.
Familiar with end-to-end MLOps practices and cloud AI services, able to deliver scalable and cost-efficient AI solutions.