Role OverviewAgileEngine is an Inc. 5000 company that creates award-winning software for Fortune 500 brands and trailblazing startups across 17+ industries. We rank among the leaders in areas like application development and AI/ML, and our people-first culture has earned us multiple Best Place to Work awards.
What You Will Do
The role combines ML infrastructure, GPU optimization, and deployment across cloud and edge environments. You 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
If you're looking for a place to grow, make an impact, and work with people who care, we'd love to meet you!
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
- 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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