MLOps Engineer - Azure AKS & Edge CV

AgileEngine, LLC.; Boston (MA); Hybrid; USD 120,000 - 180,000; Full time

Benefits offered by this job

Professional growth

Competitive compensation

Exciting projects

Flextime

Job summary

AgileEngine, LLC. in Dallas, TX is seeking an experienced MLOps Engineer to deploy, scale, and monitor computer vision models in production on Azure, handling real-time image streams from edge cameras.

You will own end-to-end deployment pipelines, drive GPU utilization and cost efficiency, and work with data scientists to translate experiments into production-ready solutions using Docker, Kubernetes, Azure AKS, and CI/CD.

Qualifications

• Authorized to work in the US with no sponsorship.
• 3+ years of professional experience in MLOps, DevOps, Data Engineering, ML, or Software Engineering.
• Degree in Computer Science, Software Engineering, or a related technical discipline.
• Based in Dallas, TX or willing to relocate; office attendance 3 days/week.
• Experience with production model serving behind REST/gRPC APIs.
• Hands-on Azure experience: AKS, Azure DevOps, and the Azure data stack.
• Experience containerizing apps with Docker and Kubernetes; strong CI/CD mindset.
• Exposure to CV/image data in production.

Responsibilities

• Lead GPU compute efficiency and infra cost-reduction strategies
• Own end-to-end deployment lifecycle from experimentation to production
• Build and scale ingestion and inference pipelines for high-volume image streams
• Architect and manage cloud and edge deployment for model inference
• Implement production monitoring, drift detection, and data lineage
• Collaborate with data scientists to productionize experiments and models

Skills

Model serving

CV in production

Azure AKS

Docker & Kubernetes

CI/CD pipelines

AI/ML fundamentals

REST/gRPC APIs

GPU compute management

Education

CS degree or related field

Tools

Azure DevOps

Azure Data Stack

TorchServe/TensorRT

ONNX

AKS

Job description

AgileEngine, LLC. in Dallas, TX is seeking an experienced MLOps Engineer to deploy, scale, and monitor computer vision models in production on Azure, handling real-time image streams from edge cameras.

You will own end-to-end deployment pipelines, drive GPU utilization and cost efficiency, and work with data scientists to translate experiments into production-ready solutions using Docker, Kubernetes, Azure AKS, and CI/CD.