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Medium: strong Tier‑1 brand and metro location, but senior specialized MLOps reduces applicant density.
Medium: core ML and MLOps skills transfer across industries, though sector experience is beneficial.
High: explicit ten-year requirement plus mandatory MLOps, cloud, frameworks, and leadership skills.
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Drive deployment, automation, maintenance, and monitoring of machine learning models in production environments.
Design, develop, and productionise advanced machine learning products and pipelines, ensuring performance and quality.
Lead and manage multi-disciplinary teams and projects across the organisation, collaborating with business stakeholders to align ML solutions with strategy.
10 years of experience in machine learning with large datasets.
Degree in STEM discipline such as Mathematics, Physics, Engineering or Computer Science.
Experience deploying ML models using CI/CD tools like TeamCity and CodeDeploy and cloud platforms like AWS, GCP, or Azure.
Work location: Must work in India (Bangalore).
Experienced in leading teams and managing complex ML projects using Agile methodologies.
Strong expertise in ML frameworks (TensorFlow, PyTorch), programming (Python), CI/CD pipelines, containerization (Docker), and version control (Git).
Capable of translating business needs into technical ML solutions and monitoring to maintain model performance and robustness.