Key Facts

Remote From:

Full time

Mid-level (2-5 years)

English

Hard Skills

MLOps (Machine Learning Operations) CI/CD Azure DevOps Kubernetes Azure Machine Learning Microsoft Azure Reliability Engineering Cloud Computing Scalability Databricks Data Management Terraform Observability Cross-Functional Collaboration Systems Architecture

Other Skills

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Collaboration
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Communication
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Problem Solving

EDI Staffing, an EDI Specialists Company

About EDI Staffing, an EDI Specialists Company

At EDI Staffing, we believe that success starts with a solid foundation: People.Through our honest, resourceful, and innovative approach to staffing, we connect organizations across all industries with the country’s most talented and reliable people.For almost 30 years, EDI Staffing has connected our clients with top talent for contract, contract-to-hire, and direct-hire needs. Between our team of experienced recruiters and our active database of over 2 million professionals across the nation, we have the expertise and resources to help you find the right people. Let us help you do your job more effectively by building a great team around you!

Founded: 2018

Company size: 11 - 50

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Job description

Job Description – Senior MLOps / DevOps Engineer

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.

Key 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

Required Skills:

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

Nice to Have: Terraform, monitoring/observability tools, ML model serving frameworks

Ready to apply?

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