Dallas MLOps Engineer - CV, GPU, Edge/Cloud

AgileEngine, LLC.; Tampa (FL); On-site; USD 120,000 - 160,000; Full time

Benefits offered by this job

Professional growth

Competitive compensation

A selection of exciting projects

Flextime

Job summary

AgileEngine, LLC. is seeking a Middle/Senior MLOps Engineer to move computer vision models from experimentation into reliable production.

You will build reproducible pipelines, monitoring, and lifecycle controls for image and video workloads using Docker, Kubernetes, and CI/CD, with onsite work in Dallas, TX. Join a people-first culture with opportunities to collaborate with data scientists and AI researchers, optimize GPU-heavy workloads, and deploy CV models to cloud and edge environments.

Qualifications

• 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
• Note: This role is focused on Computer Vision and GPU engineering; CV MLOps experience preferred

Responsibilities

• End-to-End Deployment: Own the complete lifecycle transition from AI/ML experimentation to reliable, high-performance production deployment.
• Infrastructure & Pipelines: Build, maintain, and scale the infrastructure, automation, and CI/CD workflows necessary for rapid and efficient model deployment, including large-scale image/video data ingestion, dataset versioning, and managing manual/automated image annotation workflows.
• System Stability & Monitoring: Implement robust production monitoring systems, build visibility dashboards, and set up data and concept drift detection to ensure ongoing model accuracy and system reliability.
• Model Lifecycle Management: Manage experiment tracking and model versioning to ensure full reproducibility and traceability of all models in production.
• Cross-Functional Collaboration: Partner closely with data scientists and AI researchers to translate experimental models into robust, production-ready solutions.
• Resource & Cost Optimization: Manage cloud environments and GPU compute resources to ensure systems are scalable and cost-effective, focusing on model optimization for heavy GPU workloads.
• Edge & Cloud Deployment: Deploy computer vision models to cloud environments and optimize them for Edge GPU deployment in specific use cases.

Skills

MLOps

DevOps

Data engineering

Machine learning

Software engineering

CV pipelines

Experiment tracking

Model registry/versioning

Drift detection

Production monitoring

Docker

Kubernetes

Education

Bachelor's degree in Computer Science or related field

Tools

Docker

Kubernetes

CI/CD

Job description

AgileEngine, LLC. is seeking a Middle/Senior MLOps Engineer to move computer vision models from experimentation into reliable production.

You will build reproducible pipelines, monitoring, and lifecycle controls for image and video workloads using Docker, Kubernetes, and CI/CD, with onsite work in Dallas, TX. Join a people-first culture with opportunities to collaborate with data scientists and AI researchers, optimize GPU-heavy workloads, and deploy CV models to cloud and edge environments.