.NET MLOps Specialist (ML.NET & Azure ML) - Q125

.NET MLOps Specialist (ML.NET & Azure ML) Location: Alpharetta, GA (willing to travel to client locations) Employment Type: Full-Time (W2) Role Overview We are seeking a proficient .NET MLOps Specialist to streamline machine learning workflows using ML.NET and Azure ML. This role focuses on integrating MLOps practices with .NET and C# for efficient model deployment and management. Key Responsibilities • Develop machine learning pipelines using ML.NET and C# to train, evaluate, and deploy models. • Integrate ML models into production systems with Azure ML for scalable inference and monitoring. • Automate model deployment and updates using MLOps practices and CI/CD pipelines with Azure DevOps. • Collaborate with data scientists to optimize ML workflows and ensure model accuracy and performance. • Manage model versioning, governance, and monitoring within .NET applications. • Ensure security and compliance of ML models in production environments. Required Qualifications • Bachelor's degree in Computer Science, Software Engineering, or a related field (or equivalent experience). • 3 years of experience in .NET and C# development with a focus on machine learning and MLOps. • Proficiency in building ML pipelines with ML.NET and deploying models using Azure ML. • Experience with MLOps practices, including model deployment, monitoring, and CI/CD automation. • Strong understanding of integrating ML models into production applications. Preferred Qualifications • Familiarity with Azure DevOps for automating MLOps workflows and pipeline orchestration. • Exposure to advanced ML frameworks like TensorFlow or PyTorch for integration with .NET applications. • Knowledge of cloud-based data preprocessing tools like Azure Data Factory for ML pipelines. Compensation & Benefits • Competitive salary and comprehensive benefits package (healthcare, PTO, 401k). • Opportunities for professional growth and upskilling in AI and cloud technologies. Skills: .NET, ML.NET, Azure ML, MLOps, Model Deployment, DevOps, C#, Machine Learning