DevOps Architect

Role Type: Lead DevOps Engineer with strong MLOps expertise

Location: Florida or New York

Job Summary

We are seeking an experienced Lead DevOps Engineer with strong MLOps expertise to design, implement, and automate scalable Machine Learning infrastructure on AWS. The ideal candidate will have extensive experience building and managing cloud-native ML environments, automating CI/CD pipelines, Infrastructure as Code (IaC), and supporting data science initiatives through robust MLOps practices.

This is a leadership role requiring deep expertise in AWS services, containerization, Kubernetes, and modern DevOps practices.

Key Responsibilities

• Design, build, and maintain scalable MLOps platforms on AWS.
• Automate end-to-end Machine Learning environments for model development, training, deployment, and monitoring.
• Develop and maintain CI/CD pipelines for application and ML model deployments.
• Build Infrastructure as Code (IaC) using tools such as Terraform or CloudFormation.
• Deploy and manage containerized applications using Docker, ECS, and Kubernetes (EKS preferred).
• Implement automation to support Data Science and Machine Learning initiatives.
• Integrate ML workflows with Amazon SageMaker for model training and deployment.
• Configure and manage data integrations with Snowflake.
• Monitor cloud infrastructure, optimize performance, and ensure high availability.
• Collaborate with Data Scientists, ML Engineers, and Development teams to streamline ML lifecycle management.
• Ensure security, compliance, and best practices across AWS environments.
• Provide technical leadership, mentoring, and architectural guidance to the team.

Required Skills

• 12+ years of overall IT experience.
• Strong experience as a DevOps Engineer with hands-on MLOps implementation.
• Deep expertise in Amazon Web Services (AWS).
• Hands-on experience with Amazon SageMaker.
• Strong understanding of Machine Learning Operations (MLOps) concepts and best practices.
• Experience with Infrastructure as Code (Terraform/CloudFormation).
• Expertise in CI/CD automation (Jenkins, GitHub Actions, GitLab CI, Azure DevOps, etc.).
• Strong experience with Docker, Kubernetes (EKS), and Amazon ECS.
• Experience working with Snowflake.
• Experience supporting enterprise Data Science platforms and ML pipelines.
• Strong scripting skills using Python, Bash, or similar languages.
• Excellent troubleshooting and problem-solving skills.

Preferred Skills

• Experience with ML model lifecycle management and model governance.
• Knowledge of monitoring tools such as CloudWatch, Prometheus, or Grafana.
• Experience with security best practices in AWS.
• AWS Certifications (Solutions Architect, DevOps Engineer, or Machine Learning Specialty) are a plus.
• Experience leading technical teams and driving cloud transformation initiatives.

Mandatory Skills

• AWS
• MLOps
• Amazon SageMaker
• CI/CD Automation
• Infrastructure as Code (Terraform/CloudFormation)
• Kubernetes (EKS)
• Amazon ECS
• Snowflake
• Docker
• Python/Bash
• DevOps Leadership

Work Location: Remote (Preference for candidates located in Florida or New York)