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AI Ops Engineer
Job in
Eden Prairie, Hennepin County, Minnesota, 55344, USA
Listed on 2026-06-20
Listing for:
Diverse Lynx
Full Time
position Listed on 2026-06-20
Job specializations:
-
IT/Tech
Machine Learning/ ML Engineer, AI Engineer (Applied/Software), Cloud Computing: Infrastructure & Operations, Data Engineering
Job Description & How to Apply Below
Location: Eden Prairie, MN / Remote
Job Type: Full-Time
Salary Range: $100,000 - $120,000 per year
Role Summary
The AI Ops Engineer will play a critical role in operationalizing machine learning solutions by transforming data science prototypes into scalable, production-grade ML services and pipelines. This position focuses on MLOps, model deployment, lifecycle management, monitoring, automation, and ensuring reliability of AI systems in production environments.
The ideal candidate will possess strong software engineering skills, hands-on experience with machine learning frameworks, cloud-native technologies, and a deep understanding of ML system design and operational best practices.
Must Have Technical/Functional Skills
- Strong Python programming experience.
- Hands-on experience with machine learning frameworks:
- Tensor Flow
- Py Torch
- Scikit-Learn
- Experience deploying and managing machine learning models in production environments.
- Strong understanding of MLOps principles and ML lifecycle management.
- Experience with:
- Docker
- Kubernetes
- Containerized applications
- Experience building and managing REST APIs and ML services.
- Expertise in CI/CD pipeline implementation and Dev Ops automation.
- Experience with:
- Model Tracking
- Model Registry
- Deployment Automation
- Monitoring & Observability
- Knowledge of ML system design concepts:
- Data Leakage Prevention
- Training-Serving Skew
- Model Drift Detection
- Performance Monitoring
- Experience working with feature pipelines and large-scale data processing systems.
- Strong troubleshooting, debugging, and incident response capabilities.
- Experience implementing automated testing and version-controlled ML workflows.
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