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
The MLOps Engineer will build reproducible pipelines, monitoring, and lifecycle controls for image and video workloads using Docker, Kubernetes, and CI/CD.
Why It Might Be a Fit
The role requires a strong hands-on experience with experiment tracking, model registry/versioning, drift detection, and production monitoring, as well as a solid conceptual understanding of AI/ML fundamentals.
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)
- Hands-on experience with experiment tracking, model registry/versioning, drift detection, and production monitoring
- Strong hands-on experience in CV pipelines, including training computer vision models on GPUs, dataset management, and infrastructure monitoring specific to CV model quality/drift
- 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
Benefits
- Professional growth
- Competitive compensation
- A selection of exciting projects
- Flextime
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