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Mid-level MLOps role in Bangalore with broad toolset and generalist expectations drives high applicant competition.
Core MLOps skills are transferable, but preference for retail financial-services experience increases background sensitivity.
Requires specific MLOps experience and financial-services focus, but tools and years requirements remain moderately flexible.
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Design, implement, and productionize scalable, resilient, and secure AI/ML/DL/LLM models integrated into business processes.
Maintain performance and health of deployed models and related CI/CD pipelines; automate build and deployment procedures for AI solutions.
Collaborate with data science teams and stakeholders to monitor deployments, report status, and improve models based on new data and trends.
Bachelor’s Degree in Computer Science, Engineering, or related field.
Minimum 2 years experience in AI Operations, Machine Learning Engineering, Data Science, Data Engineering, DevOps, Analytics, or related fields.
Experience with agile methodologies in retail financial services or IT fields.
Hybrid work environment requiring 6 to 8 days/month onsite presence.
Experienced in AI operations including design, deployment, and monitoring of ML/DL/LLM models in production environments.
Familiar with DevOps tools and processes including CI/CD pipelines, Docker, Azure DevOps, GitHub, and agile workflows.
Comfortable collaborating across data science, DevOps, and infrastructure teams and managing production risks and deployment scheduling.