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Strong employer brand, metro Hyderabad location, and broad ML/MLOps skillset increase candidate competition.
Core ML and MLOps skills are broadly transferable across industries, so low background sensitivity.
Explicit 8-12 years and mandatory ML, MLOps, DevOps, and cloud skills create high selection rigidity.
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Develop, train, evaluate, and scale machine learning models in collaboration with data scientists.
Build, maintain, and automate MLOps pipelines covering data ingestion, feature engineering, model training, deployment, and monitoring.
Leverage cloud platforms (AWS, GCP, Azure) and implement DevOps/MLOps best practices to ensure efficient and reliable ML workflows.
8-12 years of experience in Computer Science, IT, or related field.
Strong proficiency in machine learning algorithms, MLOps tools (e.g., MLflow, Kubeflow), and DevOps tools (e.g., Docker, Kubernetes, CI/CD).
Proficiency in Python and machine learning libraries like TensorFlow, PyTorch, or Scikit-learn.
Work Experience Required: 8-12 years as stated in the education and experience section.
Experienced in end-to-end ML lifecycle management with a strong MLOps and DevOps background.
Comfortable working with cloud platforms and automating ML workflows in production environments.
Capable of collaborating cross-functionally with data scientists, engineers, and product teams to deliver scalable ML solutions.