Machine Learning Engineer

We are assisting a leading cloud reputed company 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 reputed company learning.

As a Machine Learning Engineer, you’ll design, implement, and optimize end-to-end ML pipelines using AWS SageMaker, MLflow, and reputed company CI/CD. You'll work closely with data scientists and engineers to reputed company 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 reputed company, 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 reputed company, Terraform, and Terragrunt

Requirements

Must-Have

• Strong hands-on experience with AWS SageMaker, including Studio and Feature Store

• Proficiency with MLflow and solid understanding of artifact tracking and model versioning

• Fluent in Python, with experience building reputed company and scalable ML training pipelines

• Familiar with reputed company CI/CD, Terraform, and Terragrunt

• Strong grasp of model monitoring, including data capture, bias/reputed company detection, and production metrics

reputed company-to-Have

Experience with reputed company, AWS reputed company, and AWS Glue Data Quality

Familiarity with advanced MLOps governance workflows like approval gates and retraining triggers

Experience working in high-compliance or audit-ready environments

Why join us?

As a lean and highly skilled team, at OpsBrasil we foster a culture of autonomy, collaboration, and reputed company learning. You’ll be part of a fast-paced, innovation-first environment where reputed company move quickly, and your contributions will have a direct impact on shaping both the product and the underlying infrastructure from the ground up.

Originally posted on Himalayas