Azure MLOps Engineer

Job Description

We are seeking a Senior MLOps Engineer to lead the architecture, deployment, and operationalization of machine learning solutions in Azure-based production environments. This role is designed for a highly experienced engineer who can own end-to-end MLOps architecture, contribute immediately, and partner closely with data science, platform, and engineering teams.

This position bridges model development and enterprise-scale deployment, with a strong emphasis on Azure infrastructure, MLOps best practices, and solution design.

• Architect, deploy, and manage end-to-end MLOps solutions in Azure from development through production.
• Design and maintain Azure-native ML infrastructure, including Azure ML, Azure Dev Ops, AKS, and related services.
• Build and manage CI/CD pipelines for model training, validation, deployment, and monitoring.
• Partner with data scientists to transform research models into scalable, production-ready services.
• Develop and manage APIs and services to expose ML models across the organization.
• Implement monitoring, retraining, versioning, and governance strategies for ML models.
• Optimize compute (CPU/GPU), cost, and performance within Azure environments.
• Ensure Linux-based systems and containers are optimized for ML workloads.
• Provide architectural guidance and contribute quickly with minimal ramp-up.

Based on knowledge and years of experience, this position offers an hourly pay rate of $65-80/hr

We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances.

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• Senior-level experience in MLOps, ML engineering, or Dev Ops with ML systems.
• Strong experience architecting full ML solutions, not just deploying individual models.
• Deep Azure expertise, including:
  • Azure Machine Learning
  • Azure Dev Ops (CI/CD)
  • Azure Kubernetes Service (AKS)
  • Azure storage and networking concepts
• Strong Python and SQL skills.
• Experience with ML frameworks (PyTorch, Tensor Flow, Scikit-learn).
• Proficiency with Docker, Kubernetes, and CI/CD pipelines.
• Strong understanding of MLOps lifecycle, governance, and production best practices.
• Ability to operate independently and contribute immediately in a senior role.
• Azure certifications (Azure ML, Azure AI Engineer, or Azure Solutions Architect).
• Experience optimizing ML workloads using GPUs/CPUs in Azure.
• Strong understanding of ML theory, algorithms, and data science concepts.
• Experience supporting multiple ML systems in production environments.