MLOps Engineer

About the role

We are looking for an MLOps Engineer to deploy, scale, and monitor computer vision models in production on Azure , processing real-time image streams from thousands of edge cameras.

The mandatory requirements are being based in Dallas, TX, or open to relocating there, availability to work onsite 3 days a week, production model serving with Triton Inference Server, TorchServe, KServe, or Azure ML endpoints, hands-on experience with computer vision or image data in production, Azure (AKS and Azure DevOps) , 3+ years of experience in MLOps, DevOps, ML, or software engineering, Docker, Kubernetes, CI/CD, and an upper-intermediate English level.

Must haves

• 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).
• Must be based in Dallas, TX, or open to relocating to Dallas. Office attendance: 3 days/week.
• MLOps Core: Production model serving ( Triton Inference Server, TorchServe, KServe, or Azure ML endpoints ) behind REST/gRPC APIs, with end-to-end backend pipeline ownership. Exposure to tracking, model registry/versioning, drift detection, and production telemetry/monitoring.
• Computer Vision: Working exposure to CV/image data in production.
• Infrastructure & Cloud: Strong practical experience navigating cloud environments, strictly focused on Azure , specifically using AKS for deployment, Azure DevOps, and the Azure data stack, alongside managing/provisioning GPU compute resources.
• DevOps & Automation: Deep understanding of containerization (e.g., Docker and Kubernetes ) and designing robust CI/CD pipelines for automated deployments.
• AI/ML Foundation: A solid conceptual understanding of AI/ML fundamentals to effectively communicate, troubleshoot, and collaborate with applied model developers.
• Upper-intermediate English level.

What you will do

• Resource & Cost Optimization: Lead GPU compute efficiency and infrastructure cost-reduction strategies by optimizing models to maximize camera throughput per GPU. Apply optimization techniques including quantization (FP16/INT8), pruning, TensorRT/ONNX conversion, dynamic batching, and GPU autoscaling on AKS.
• 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 robust ingestion and inference pipelines for high-volume image streams using Azure Data Factory, cloud storage, and automated CI/CD workflows.
• Edge & Cloud Deployment: Architect and manage large-scale cloud-based model inference environments, with secondary support for edge GPU deployment across specific edge use cases.
• 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.

Perks

• 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