Machine Learning Engineer

Remote, USA
Posted Jun 14, 2026
Full-time

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

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 modular and scalable ML training pipelines

    Familiar with GitLab CI/CD, Terraform, and Terragrunt

    Strong grasp of model monitoring, including data capture, bias/drift detection, and production metrics

Nice-to-Have

Experience with Snowflake, AWS Athena, 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 continuous learning. You’ll be part of a fast-paced, innovation-first environment where ideas 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

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