Remote MLOps Engineer - Scale AI Deployments

AgileEngine, LLC.; Baltimore (MD); On-site; USD 140,000 - 190,000; Full time

Benefits offered by this job

Growth without limits

Competitive compensation

Flexibility: 100% remote with flexible

Meaningful modern projects

Collaborative culture

Well-being and support

Job summary

AgileEngine is seeking a Middle/Senior MLOps Engineer to own end-to-end ML deployment, from experimentation to production, building robust infrastructure and CI/CD for scalable model delivery. You will implement monitoring, drift detection, and versioning while collaborating with data scientists to translate experiments into production-ready solutions.

Role requires 3+ years in MLOps/DevOps or related fields, a CS/engineering degree (or equivalent), and onsite work in Dallas, TX.

Qualifications

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

Responsibilities

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

Skills

MLOps

DevOps

Data Engineering

Machine Learning

Software Engineering

Experiment tracking

Model registry/versioning

CI/CD pipelines

Cloud environments

GPU compute

Docker

Kubernetes

Education

Computer Science

Tools

Docker

Kubernetes

CI/CD tooling

Job description

AgileEngine is seeking a Middle/Senior MLOps Engineer to own end-to-end ML deployment, from experimentation to production, building robust infrastructure and CI/CD for scalable model delivery. You will implement monitoring, drift detection, and versioning while collaborating with data scientists to translate experiments into production-ready solutions.

Role requires 3+ years in MLOps/DevOps or related fields, a CS/engineering degree (or equivalent), and onsite work in Dallas, TX.