MLOps SME

Job highlights

• Mandatory Skills . Strong experience in MLOps and Machine Learning. . Python programming. . AWS Bedrock and AWS SageMaker - both mandatory. . End-to-end ML model deployment and monitoring. . Strong communication and problem-solving skills

MLOps SME

Roles and Responsibilities

• Design, develop, and deploy end-to-end MLOps pipelines.
• Build and optimize machine learning models using Python.
• Work hands-on with AWS Bedrock and AWS SageMaker.
• Implement model deployment, monitoring, versioning, and retraining workflows.
• Develop CI/CD pipelines for automated ML deployment.
• Use Docker and Kubernetes for containerization and deployment.
• Collaborate with data science, engineering, and business teams.
• Provide technical guidance and act as a subject matter expert (SME).
• Ensure scalability, reliability, and performance of production ML solutions.

Mandatory Skills

• Strong experience in MLOps and Machine Learning.
• Python programming.
• AWS Bedrock and AWS SageMaker - both mandatory.
• End-to-end ML model deployment and monitoring.
• Strong communication and problem-solving skills.

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

Disclaimer: The job location mentioned in this description is based on publicly available information or company headquarters. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.