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Bangalore metro plus popular entry ML role increases competition, but strict IIT/NIT and CGPA filters limit pool.
Core ML/MLOps skills are transferable, though healthcare data/regulatory exposure adds moderate domain specificity.
Strict institute and CGPA requirements plus mandatory ML project and explicit years make filters high.
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Develop and deploy production-grade Python and SQL code for high-volume, sensitive healthcare data systems, including ML and AI pipelines.
Convert models and features from design/notebooks into reliable, scheduled, monitored production services and own them post-deployment.
Build and maintain evaluation metrics, monitoring, logging, and reproducibility frameworks to ensure trustworthy production systems; troubleshoot live issues and optimize for cost, latency, and reliability.
Bachelor's degree in Computer Science, Information Technology or related field from IITs, NITs, or premier engineering institutes.
Minimum 0-1 years of relevant experience in software engineering or machine learning.
Strong proficiency in Python (organized, version-controlled, tested code) and fluency in SQL with experience handling real, messy datasets.
Aggregate CGPA of 8.0 or above; Requirement to handle sensitive healthcare data and production ML/AI systems.
Experience with building at least one deployed ML/AI system beyond notebooks, including data or feature pipelines or working RAG/agent prototypes.
Depth in one focus area: Applied ML and evaluation; MLOps and cloud/deployment tooling; or LLMs, RAG, and agentic frameworks.
Familiarity with major cloud platforms and containerized deployment, and exposure to orchestration tools, feature stores, or experiment tracking is a plus.