Senior AWS SageMaker / MLOps Engineer

Job summary

Develop, train, deploy, and monitor machine learning models using AWS SageMaker. Build and manage feature engineering workflows and use the AWS SageMaker Feature Store as part of MLOps and Python development.

Job details

Top 3 Required Skills: AWS SageMaker (Model Development, Training, Deployment, Monitoring) AWS SageMaker Feature Store and Feature Engineering MLOps and Python Development

What you’ll do

Develop, train, deploy, and monitor machine learning models using AWS SageMaker. Build and manage feature engineering workflows and use the AWS SageMaker Feature Store as part of MLOps and Python development.

Requirements

The role requires experience with AWS SageMaker across model development, training, deployment, and monitoring. It also requires knowledge of the SageMaker Feature Store, feature engineering, MLOps, and Python development.

Listed skills

• Amazon Web Services · Preferred
• Python · Preferred
• Machine learning · Preferred
• Development · Preferred
• Training · Preferred
• Organization · Preferred
• Attention to detail · Preferred

Other relevant skills

Identified from the job description. Confirm important requirements above.

• AWS SageMaker
• Model Development
• Model Training
• Model Deployment
• Model Monitoring
• AWS SageMaker Feature Store
• Feature Engineering
• MLOps
• Python Development

Job areas

• Technology
• Software
• Data & Analytics
• Consulting

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