Role OverviewWe are looking for a Middle/Senior MLOps Engineer to move computer vision models from experimentation into reliable production. The role combines ML infrastructure, GPU optimization, and deployment across cloud and edge environments.
What You Will Do
- 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 not only highly scalable but also cost-effective, focusing on model optimization for heavy GPU workloads, including latency, throughput, batching, and GPU memory utilization. - Edge & Cloud Deployment: Deploy computer vision models to cloud environments and optimize them for Edge GPU deployment in specific use cases.
Why It Might Be a Fit
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). - Engineers located in the US must reside in Dallas, TX, and be willing to work onsite.
Requirements
- Authorized to work for ANY employer in the US
- 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)
- Reside in Dallas, TX, and be willing to work onsite
Benefits
- Professional growth
- Competitive compensation
- A selection of exciting projects
- Flextime
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