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Tier-1 brand, metro Bengaluru location, and mid-level DevOps/MLOps title increase candidate competition.
DevOps/MLOps skills transfer across industries but expect cloud and model operationalization experience.
Explicit 3+ years plus mandatory AWS, CI/CD, SageMaker/EKS stack creates strict technical filters.
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Build and maintain CI/CD pipelines for machine learning workflows enabling rapid, automated deployment.
Operationalize ML models from prototype to scalable, real-time production APIs using AWS services like SageMaker, EKS, and Lambda.
Provision and manage AWS infrastructure tailored for ML training, inference, and monitor model performance including data drift and latency.
3+ years of experience in relevant DevOps and MLOps roles.
Bachelor's degree or higher in Engineering, MCA, MBA, or equivalent full-time qualifications (no course extension due to backlogs).
Strong knowledge and hands-on skills with AWS DevOps tools, Container Orchestration, CloudFormation, and UNIX shell scripting.
Work Experience Required: 3+ years
Experienced in collaborating with data scientists and DevOps teams to optimize and operationalize machine learning models.
Skilled in building end-to-end CI/CD pipelines specifically for machine learning and AI workflows.
Comfortable working in advisory or enterprise architecture environments focused on operationalizing cloud-based ML solutions and ensuring security and compliance.