MLOps Engineer ID72409

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 is an Inc. 5000 company that creates award-winning software for Fortune 500 brands and trailblazing startups across 17+ industries. We rank among the leaders in areas like application development and AI/ML, and our people-first culture has earned us multiple Best Place to Work awards.

WHY JOIN US

If you're looking for a place to grow, make an impact, and work with people who care, we'd love to meet you!

ABOUT THE ROLE

We are looking for a Middle/Senior MLOps Engineer to own the complete lifecycle transition from AI/ML experimentation to reliable production deployment, building and maintaining the infrastructure, pipelines, and automation needed to deploy models efficiently at scale. You will implement production monitoring systems, drift detection, experiment tracking, and model versioning, while managing cloud environments and GPU compute resources for cost-effective scalability. 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.

WHAT YOU WILL DO

• 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 not only highly scalable but also cost-effective.

MUST HAVES

• You must be authorized to work for ANY employer in the US (e.g., Green card holders, TN visa holders, GC EAD, H4 EAD, U4U with EAD), as we are unable to sponsor or take over employment visa sponsorship at this time;
• 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;
• Upper-intermediate English level.

PERKS AND BENEFITS

• Growth without limits: build your skills through mentorship, internal TechTalks, challenging projects, and a dedicated annual learning budget
• Competitive compensation: get recognition that reflects your skills and impact, with regular performance and compensation reviews
• Flexibility: work 100% remotely with flexible hours that support focus, autonomy, and a healthy work rhythm
• Meaningful, modern projects: build impactful products using modern technologies alongside global teams and leading brands
• Collaborative culture: join a supportive environment with zero micromanagement where ideas are welcomed and contributions are recognized
• Well-being & support: access local well-being programs and people-focused support tailored to your location