Remote MLOps Engineer: Scale Production ML & CI/CD

AgileEngine, LLC.; Arkansas; On-site; USD 120,000 - 180,000; Full time

Benefits offered by this job

Growth budget

Competitive pay

Remote work

Modern projects

Collaborative culture

Well-being programs

Job summary

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

You will collaborate with data scientists to translate experimental models into production-ready solutions, while managing cloud environments and GPU resources for cost-effective scalability. Dallas, TX onsite.

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
• Hands-on experience with experiment tracking, model registry/versioning, drift detection, and production monitoring
• Strong practical experience navigating cloud environments and managing/provisioning GPU compute resources
• Deep understanding of containerization (e.g., Docker, Kubernetes) and designing robust CI/CD pipelines for automated deployments
• A solid conceptual understanding of AI/ML fundamentals to effectively communicate, troubleshoot, and collaborate with applied model developers

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 necessary for rapid and efficient model deployment
• Implement robust production monitoring systems, build visibility dashboards, and set up data and concept drift detection to ensure ongoing model accuracy and system reliability
• Manage experiment tracking and model versioning to ensure full reproducibility and traceability of all models in production
• Partner closely with data scientists and AI researchers to translate experimental models into robust, production-ready solutions
• Manage cloud environments and GPU compute resources to ensure systems are scalable and cost-effective

Skills

MLOps/DevOps

Cloud environments

Experiment tracking

Model versioning

Education

Bachelor's degree in Computer Science, Software Engineering, or related technical discipline

Tools

Docker

Kubernetes

CI/CD

Job description

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

You will collaborate with data scientists to translate experimental models into production-ready solutions, while managing cloud environments and GPU resources for cost-effective scalability. Dallas, TX onsite.