Remote MLOps Engineer: Scale AI Deployments & Pipelines

AgileEngine, LLC.; Town of Vermont (WI); On-site; USD 140,000 - 190,000; Full time

Benefits offered by this job

Growth without limits

Competitive compensation

Remote flexibility: 100% remote with a

Modern projects

Collaborative culture

Well-being programs

Job summary

AgileEngine is seeking a Middle/Senior MLOps Engineer to own the lifecycle from AI/ML experimentation to production deployment. You will build and maintain infrastructure, pipelines, and automation for scalable model deployment, with production monitoring, drift detection, experiment tracking, and model versioning.

Role requires cloud experience, GPU resources management, and collaboration with data scientists to translate experiments into robust solutions.

Qualifications

• 3+ years of professional experience in MLOps, DevOps, Data Engineering, Machine Learning, or Software Engineering.
• Degree in Computer Science, Software Engineering, or a related technical discipline (or equivalent practical experience).
• Engineers located in the US must reside in Dallas, TX and be willing to work onsite.

Responsibilities

• Own the complete lifecycle transition from AI/ML experimentation to reliable, high-performance production deployment.
• Build, maintain, and scale the infrastructure, automation, and CI/CD workflows for rapid model deployment.
• Implement production monitoring systems, dashboards, and drift detection to ensure model accuracy and system reliability.
• Manage experiment tracking and model versioning for full reproducibility and traceability of models in production.
• Collaborate with data scientists and AI researchers to translate experimental models into production-ready solutions.
• Manage cloud environments and GPU compute resources for scalable and cost-effective systems.

Skills

MLOps

DevOps

Data engineering

Machine learning

Software engineering

Docker

Kubernetes

CI/CD

Cloud environments

Education

Bachelor's or higher in Computer Science / Software Engineering or related

Tools

Docker

Kubernetes

CI/CD pipelines

Cloud platforms (AWS/GCP/Azure)

Job description

AgileEngine is seeking a Middle/Senior MLOps Engineer to own the lifecycle from AI/ML experimentation to production deployment. You will build and maintain infrastructure, pipelines, and automation for scalable model deployment, with production monitoring, drift detection, experiment tracking, and model versioning.

Role requires cloud experience, GPU resources management, and collaboration with data scientists to translate experiments into robust solutions.