Description

You will design, develop, and deploy machine learning models within an AWS environment.

Responsibilities

• Build, train, and fine-tune supervised and unsupervised machine learning models using Amazon SageMaker or custom frameworks.
• Design and maintain data pipelines for efficient collection, transformation, and storage using AWS Glue, EMR, and Redshift.
• Scale machine learning workflows and automate tasks to improve efficiency and reduce manual intervention.
• Conduct A/B testing, model validation, and experimentation to assess performance and derive insights.
• Collaborate with data engineers, DevOps, and product teams to define requirements and deliver data science solutions.

Required Skills

• 8+ years of experience in data science or related machine learning roles.
• Hands-on experience with Amazon SageMaker for model development and deployment.
• Proficiency in managing large-scale datasets using AWS S3 and AWS Glue.
• Experience with AWS EMR and AWS Redshift for data processing and integration.
• Ability to implement machine learning models using AWS Lambda.
• Knowledge of AWS security best practices and governance frameworks for data management.
• Experience designing and maintaining automated data pipelines.

Preferred Skills

• Experience with model optimization and performance tuning in cloud environments.

Key Skills

Education

Any Gradute