MLOps Engineer — Scale ML Deployments & Observability

AgileEngine, LLC.; Austin (TX); On-site; USD 120,000 - 180,000; Full time

Benefits offered by this job

Growth without limits

Competitive compensation

Remote flexibility

Modern projects

Collaborative culture

Well-being & support

Job summary

AgileEngine, LLC seeks a Middle/Senior MLOps Engineer to own the complete lifecycle 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.

The role is based onsite in Dallas, TX, and requires close collaboration with data scientists and AI researchers to translate experimental models into production-ready solutions.

Qualifications

• Authorized to work in the US without sponsorship.
• 3+ years of professional MLOps/DevOps experience.
• Degree in Computer Science, Software Engineering, or related technical discipline.
• Dallas, TX onsite work location.
• Hands-on with experiment tracking, model versioning, drift detection, and production monitoring.
• Strong cloud experience and GPU resource provisioning.
• Knowledge of Docker, Kubernetes, and CI/CD pipelines.
• Solid understanding of AI/ML fundamentals.

Responsibilities

• Own the lifecycle transition from experimentation to production deployment.
• Build, maintain, and scale infrastructure, automation, and CI/CD for model deployment.
• Implement production monitoring, dashboards, and drift detection.
• Manage experiment tracking and model versioning for reproducibility.
• Collaborate with data scientists to productionize models.
• Manage cloud environments and GPU resources for cost-efficient scaling.

Skills

MLOps experience

DevOps

Experiment tracking

Model versioning

Drift detection

CI/CD pipelines

Docker

Kubernetes

Cloud environments

GPU compute

AI/ML fundamentals

Education

Computer Science degree

Tools

Docker

Kubernetes

AWS

GCP

Git

Job description

AgileEngine, LLC seeks a Middle/Senior MLOps Engineer to own the complete lifecycle 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.

The role is based onsite in Dallas, TX, and requires close collaboration with data scientists and AI researchers to translate experimental models into production-ready solutions.