MLOps Engineer — Flexible Hours, High-Impact Production

AgileEngine; Plano (TX); On-site; USD 110,000 - 170,000; Full time

Benefits offered by this job

Growth without limits

Competitive compensation

Flexibility: 100% remote with flexible

Meaningful, modern projects

Collaborative culture

Well-being & support

Job summary

AgileEngine in Dallas, TX, is seeking a Middle/Senior MLOps Engineer to own the full lifecycle from experimentation to production deployment. You will build and maintain infrastructure, pipelines, and automation for scalable model delivery and cost-efficient GPU usage.

Collaborate with data scientists and AI researchers to translate experiments into production-ready solutions, implement monitoring, drift detection, and model versioning, while managing cloud environments on-site in Dallas.

Qualifications

• 3+ years of professional experience in MLOps, DevOps, Data Engineering, ML, or Software Engineering.
• Degree in CS/Software Eng or equivalent.
• US on-site in Dallas, TX and authorized to work in US.

Responsibilities

• Own end-to-end lifecycle from AI/ML experiments to production deployment.
• Build and scale infrastructure, automation, and CI/CD for model deployment.
• Implement production monitoring and drift detection for model accuracy.
• Manage experiment tracking and model versioning for reproducibility.
• Collaborate with data scientists to translate experiments into production.
• Manage cloud environments and GPU resources for cost-effective scaling.

Skills

MLOps / DevOps experience

CI/CD and automation

Collaboration with data science teams

English communication

Education

Bachelor's degree in Computer Science or related field

Tools

Docker

Kubernetes

Terraform

CI/CD tooling

Job description

AgileEngine in Dallas, TX, is seeking a Middle/Senior MLOps Engineer to own the full lifecycle from experimentation to production deployment. You will build and maintain infrastructure, pipelines, and automation for scalable model delivery and cost-efficient GPU usage.

Collaborate with data scientists and AI researchers to translate experiments into production-ready solutions, implement monitoring, drift detection, and model versioning, while managing cloud environments on-site in Dallas.