AWS SageMaker

Role: AWS SageMaker Engineer
Location: Atlanta GA / Charlotte NC (Hybrid 3 days onsite initially then full onsite)
Experience: 3 5 Years (relevant in AWS SageMaker / MLOps)
Visa: W2 Only & Locals No relocation

Job Description:

We are seeking a skilled AWS SageMaker Engineer to join our team supporting Truist Bank through Cognizant. The ideal candidate will have hands-on experience building deploying and managing machine learning models using AWS SageMaker and related AWS cloud services.

Responsibilities:

• Design develop and deploy ML models on AWS SageMaker.
• Build and maintain end-to-end ML pipelines including data preprocessing model training evaluation and deployment.
• Collaborate with Data Scientists and Engineers to optimize model performance and scalability.
• Manage model versioning monitoring and retraining workflows using MLOps best practices.
• Implement security governance and automation for ML workloads in AWS.
• Troubleshoot and resolve issues related to data ingestion model training and deployment pipelines.
• Document processes and assist in creating reusable components and templates.

Required Skills:

• 3 5 years of experience with AWS SageMaker (end-to-end ML lifecycle).
• Solid understanding of Python Boto3 and AWS SDKs.
• Experience with AWS services such as Lambda S3 EC2 ECS ECR Glue Step Functions and CloudFormation.
• Familiarity with CI/CD pipelines for ML (CodePipeline Jenkins or similar).
• Knowledge of containerization (Docker) and model deployment in production environments.
• Understanding of data engineering concepts (ETL feature store data prep).

Good to Have:

• Experience with MLflow Kubeflow or Vertex AI.
• Prior work in banking or financial domain.
• Exposure to DataBricks or Snowflake integration with SageMaker.

Soft Skills:

• Strong analytical and problem-solving abilities.
• Excellent communication and teamwork skills.
• Self-starter with ability to work in a fast-paced hybrid environment.