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Strong Tier-1 employer, Bangalore metro, popular ML role with broad MLops/CV requirements.
Highly specialized MLops and computer vision requirements limit cross-industry transferability.
Explicit 8-10 years requirement plus mandatory MLops, cloud, deployment, and CV expertise.
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Design, build, and deploy sophisticated machine learning models focusing on automation and CI/CD pipelines using tools like MLflow, Kubeflow, or SageMaker.
Architect and maintain scalable ML infrastructure on cloud platforms (AWS, Azure, GCP), ensuring optimized resource use and real-time inference capabilities.
Implement monitoring for model performance, governance, and compliance; lead integration of ML solutions and mentor junior engineers.
Bachelor’s or Master’s degree in Computer Science, Data Engineering, or related field.
8-10 years of experience in software engineering, data science, or ML Ops.
Strong proficiency in Python, Docker, Kubernetes, and cloud-native ML tools including experience with ML lifecycle platforms like MLflow or TFX.
Must have experience with CI/CD for ML, deployment strategies, and model monitoring tools.
Experienced in productionizing end-to-end ML workflows, especially in Computer Vision or domain-specific ML applications.
Capable of leading infrastructure design for scalable, distributed training, and real-time inference in cloud environments.
Demonstrates expertise in ML lifecycle management including model versioning, compliance, and cost optimization in a global corporate setting.