Machine Learning Engineer

We are assisting a leading cloud consulting firm specializing in cloud-native development, data and AI modernization, and secure cloud operations. As an AWS Premier Partner, they help organizations scale with cutting-edge technologies while fostering a culture of innovation, collaboration, and continuous learning.

As a Machine Learning Engineer, you’ll design, implement, and optimize end-to-end ML pipelines using AWS SageMaker, MLflow, and GitLab CI/CD. You'll work closely with data scientists and engineers to make sure models are trained, shipped, and monitored with performance, governance, and reliability in mind.

What you’ll be doing

• Build and maintain training pipelines using the AWS SageMaker SDK, with MLflow for experiment tracking

• Own the full model lifecycle: tracking, packaging, versioning, and registry management

• Implement and monitor real-time (SageMaker Endpoints) and batch (Batch Transform) inference pipelines

• Integrate model predictions with DynamoDB to support third-party enrichment and real-time workflows

• Set up monitoring for data drift, bias detection, and overall model health using SageMaker Model Monitor

• Maintain the MLflow Model Registry to ensure versioned, production-approved models

• Collaborate with the DevOps/infrastructure team to manage CI/CD/CT pipelines using GitLab, Terraform, and Terragrunt