Senior MLOps / DevOps Engineer
DevOps
DevOps
Hyattsville , Maryland Contract Apr 16, 2026
Senior MLOps / DevOps Engineer
Location: Remote / EST
Duration: 6-month contract with extensions
Pay: $65+/hr
Job Description
Our Retail client with over $80B in annual revenue has over 2,000 stores, across 21 US states, with over 400,000 employees. This company is a leader in sustainable retailing with a passion for delivering excellence. By driving omni channel growth, efficiency in the shopping experience and continuing to develop with new technologies; this company is growing and developing continuing success. The leadership team strives for work-life balance for all its employees, with options for overtime if desired.
We are looking for a Senior MLOps/DevOps Engineer to support the design, implementation, and maintenance of scalable ML and data platform solutions on Azure. This role will drive best practices in CI/CD, Kubernetes-based deployments, and MLOps, enabling reliable and efficient model development and deployment.
Responsibilities
Location: Remote / EST
Duration: 6-month contract with extensions
Pay: $65+/hr
Job Description
Our Retail client with over $80B in annual revenue has over 2,000 stores, across 21 US states, with over 400,000 employees. This company is a leader in sustainable retailing with a passion for delivering excellence. By driving omni channel growth, efficiency in the shopping experience and continuing to develop with new technologies; this company is growing and developing continuing success. The leadership team strives for work-life balance for all its employees, with options for overtime if desired.
We are looking for a Senior MLOps/DevOps Engineer to support the design, implementation, and maintenance of scalable ML and data platform solutions on Azure. This role will drive best practices in CI/CD, Kubernetes-based deployments, and MLOps, enabling reliable and efficient model development and deployment.
Responsibilities
- CI/CD pipeline design and automation using Azure DevOps
- Architect and manage Kubernetes (AKS) environments for ML workloads
- Enable end-to-end MLOps workflows across Azure ML and Databricks
- Partner with Data Science and Engineering teams to improve scalability, reliability, and security
- Strong expertise in Azure DevOps, CI/CD, and Kubernetes (AKS)
- Experience with Azure cloud, Azure ML, and Databricks
- Solid understanding of MLOps and ML lifecycle in production environments
- Terraform, monitoring/observability tools, ML model serving frameworks
Category Code: JN008
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