MLOps Engineer ID72409

Role Overview

AgileEngine is hiring a Middle/Senior MLOps Engineer to own the end-to-end lifecycle transition from AI/ML experimentation to reliable production deployment. You will build and maintain the infrastructure, pipelines, and automation needed to deploy models efficiently at scale.

Responsibilities

• Own the lifecycle transition from experimentation to high-performance production deployment
• Build, maintain, and scale infrastructure, automation, and CI/CD workflows for rapid model deployment
• Implement production monitoring, visibility dashboards, and data/concept drift detection
• Manage experiment tracking and model versioning/model registry for reproducibility and traceability
• Collaborate with data scientists and AI researchers to productionize experimental models
• Manage cloud environments and GPU compute resources for scalable and cost-effective operations

Requirements (Must Have)

• US work authorization (no current visa sponsorship available)
• Experience in MLOps / DevOps / Data Engineering / Machine Learning / Software Engineering
• Degree in CS/Software Engineering or equivalent practical experience
• Based in Dallas, TX and willing to work onsite
• Hands-on experience with: experiment tracking, model registry/versioning, drift detection, and production monitoring
• Strong cloud experience, including provisioning/managing GPU compute
• Deep understanding of containerization (Docker, Kubernetes) and designing CI/CD pipelines for automated deployments
• Solid conceptual understanding of AI/ML fundamentals
• Upper-intermediate English

Nice-to-Haves / Benefits

• Mentorship, TechTalks, and personalized growth roadmaps
• USD-based compensation plus education/fitness/team activity budgets
• Flexible schedule with remote and office options (while the role is onsite in Dallas)