Description

You will manage the deployment and optimization of machine learning models within an AWS cloud environment.

This role is on-site.

Responsibilities

• Deploy and optimize ML models in AWS, focusing on scalability and performance.
• Design and engineer data solutions and efficient ETL pipelines to ensure smooth data flow.
• Collaborate with data scientists to adjust and optimize ML models and queries.
• Address data latency issues and manage data processing delays.
• Implement CI/CD and DevOps automation using Jenkins and Terraform.

Required Skills

• 5+ years of experience in Python software development and building data pipelines.
• Extensive experience deploying ML models using AWS SageMaker and Lambda.
• Proficiency with AWS services including SQS, SNS, Athena, Glue, and ECR.
• Strong ETL skills for data transformation, cleaning, and preparation.
• Hands-on experience with CI/CD pipelines and DevOps automation via Jenkins and Terraform.
• Background in data engineering with specific experience in MLOps.
• Proven experience contributing to AI, machine learning, or deep learning projects.

Preferred Skills

• AWS Certifications: Machine Learning – Specialty, Solutions Architect, or DevOps Engineer.
• Experience with advanced deep learning frameworks.

Key Skills

Education

Any Gradute