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Tier-1 brand, popular ML role, early-mid level, and metro location increase competition.
Requires ML/DL and MLOps expertise, making cross-industry transfer moderately sensitive.
Multiple mandatory ML, cloud, deployment, and production-support skills raise shortlist strictness.
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Design, develop, deploy, and support AI and machine learning models and production-grade cognitive microservices primarily using Python and Azure technologies.
Manage the end-to-end lifecycle of AI/ML projects including data exploration, preprocessing, feature engineering, model development, deployment, and production support.
Collaborate cross-functionally with data scientists, ML engineers, software engineers, and business stakeholders to identify AI use cases and deliver scalable solutions.
Strong hands-on expertise in Python and associated ML/AI libraries including scikit-learn, Pandas, Numpy, and PyTorch.
Experience with machine learning model development, data preprocessing, feature engineering, statistical analysis, and data visualization.
Work Experience Required: Minimum 1 year professional experience or education in statistics, data science, machine learning, AI, computer science, or related discipline.
Experience with cloud platforms (preferably Azure), SQL/MySQL databases, and production support including incident investigation and root cause analysis.
Experienced in deploying and maintaining containerized machine learning services or cognitive microservices on Azure, including usage of Azure Kubernetes Service (AKS).
Strong understanding of Generative AI models and applications, including concepts like prompt engineering, embeddings, and responsible AI.
Capable of automating workflows and integrating end-to-end AI solutions, including knowledge of DevOps/MLOps practices and API/microservices architecture.