MLOPS Cloud Engineer

Job Title : MLOPS Cloud Engineer

Location : Charlotte, NC (hybrid)

Duration : 18 Month

Job Summary

We are seeking an Advanced MLOps Engineer to architect and scale our machine learning platform on AWS. This is a DevOps/Platform coding role focused on enabling data scientists. The successful candidate will combine an advanced understanding of the ML lifecycle with a consultant mindset to build reliable, high-volume data pipelines and robust infrastructure using IaC.

Job Responsibilities

Key Responsibilities

Platform Architecture: Design and maintain the end-to-end cloud platform, leveraging AWS services (SageMaker, Bedrock, EKS, Step Functions, Lambda) for security and scalability.

Data Pipeline Engineering: Develop and optimize Python-based, high-volume data pipelines to transform and prepare data at scale for model consumption.

MLOps & Automation: Implement MLOps best practices (MLFlow) for model tracking and deployment. Build and own CI/CD using GitHub Actions and manage platform configuration in JIRA/Agile.

Infrastructure as Code (IaC): Own all infrastructure provisioning and management using expert-level proficiency in Terraform.

Consulting: Act as a technical consultant to Data Science teams, building custom tools and solutions to accelerate their path to production.

Required Skills & Qualifications

ML Expertise: Advanced understanding of the AI/ML lifecycle, concepts, and deployment patterns.

Cloud & IaC: Expert in AWS platform services and Terraform.

Programming & Tooling: Strong Python platform coding, experience with MLFlow, GitHub, and GitHub Actions.

Process: Familiarity with software development best practices and Agile methodologies.

Preferred: Prior experience in a Solutions Architect (SA) capacity.