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Mid-level ML role in Bangalore with popular title and broad MLOps/data skill requirements increases competition.
MLOps, Azure and big-data skills are transferable but require specific ML/platform experience, so moderate sensitivity.
Explicit 5–7 years requirement plus many mandatory MLOps, cloud, and data stack skills increases filtering strictness.
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Develop and deploy end-to-end data integration and analytics solutions, including data ingestion, processing, and ML productization on AKS clusters.
Own data platform operations, MLOps platform, and data lake stack, ensuring deployment and support of customer-facing projects with CI/CD automation (GitLab, Helm).
Translate business requirements into scalable data pipelines and advanced analytics tools to deliver actionable business insights and improve decision-making.
5-7 years experience developing data applications and software for data processing using Python/Pyspark and big data technologies.
Degree in Computer Science or Engineering mandatory.
Proficient in Python programming, SQL & NoSQL databases, Azure cloud services, AKS, Kafka, Docker, and data visualization tools like Power BI or Tableau.
Experience with CI/CD pipelines using GitLab/Helm and deploying ML pipelines in complex heterogeneous environments.
Experienced in designing and delivering enterprise-grade cloud data architectures and data integration patterns, especially on Azure PaaS solutions.
Skilled in building scalable data ingestion and processing pipelines suitable for machine learning and BI consumption with strong operational ownership.
Comfortable handling end-to-end MLOps platform production deployments including data security (RBAC, IAM) and cost optimization aligned with client strategic goals.