Azure MLOps Platform Engineer

Location: Bellevue, WA

Long Term

Must have -

• 5 Plus years of Strong expertise in Azure Machine Learning Service (AMLS), Kubernetes (AKS), and MLOps practices.

• Hands-on experience in automating ML pipelines, including CI/CD integration and model lifecycle management.

• Proficiency in programming languages like Python and familiarity with Spark and PySpark for data processing.

• Solid understanding of Azure Synapse, Azure Data Factory, and resource optimization techniques.

• Experience in monitoring and troubleshooting production ML environments with zero downtime.

• Strong problem-solving skills, compliance knowledge (Safe Secret), and the ability to work across cross-functional teams.

• Familiarity with GPT model integration and AI research initiatives.

• Knowledge of containerization and microservices architecture for scalable ML solutions.

• Experience in cost-saving strategies and optimizing cloud infrastructure.

• Understanding of cloud-native deployment using DevOps tools such as Azure DevOps, Git, and CI/CD pipelines.

• Strong knowledge of PowerShell for scripting and automation.

• Experience with DevOps practices, including tools like Azure DevOps, Git, and CI/CD pipelines.

Good to Have:

• Hands-on expertise with MLflow for managing ML lifecycles, including tracking, packaging, and model deployment.
• Proficiency in deploying ML models using Azure Machine Learning Service (AMLS) integrated with Kubernetes (AKS) for scalable production environments.
• Implementation of automated pipelines for model monitoring, drift detection, and periodic retraining