About the Role: We are seeking a highly experienced Senior Machine Learning Architect with deep expertise in designing, deploying, and scaling ML solutions on Microsoft Azure. This role is ideal for a strategic thinker who can bridge the gap between data science, engineering, and cloud architecture to deliver enterprise-grade AI/ML solutions. Key Responsibilities: • Architect and Design ML Solutions: • Lead the end-to-end architecture of scalable machine learning systems using Azure services. • Define ML system components including data ingestion, model training, deployment, monitoring, and governance. • Azure ML Platform Expertise: • Leverage Azure Machine Learning, Azure Databricks, Azure Synapse Analytics, and Azure Data Lake for model development and deployment. • Implement MLOps pipelines using Azure DevOps, MLflow, and GitHub Actions. • Model Lifecycle Management: • Oversee model versioning, reproducibility, and CI/CD for ML models. • Ensure robust model monitoring, drift detection, and retraining strategies. • Collaboration & Leadership: • Partner with data scientists, engineers, and business stakeholders to translate business problems into ML solutions. • Mentor junior architects and data scientists on best practices in ML and cloud-native development. • Security & Compliance: • Ensure all ML solutions comply with enterprise security, privacy, and governance standards. • Implement responsible AI practices and model explainability using Azure Responsible AI tools. Required Qualifications: • 8+ years of experience in data science, machine learning, or AI. • 3+ years of experience architecting ML solutions on Microsoft Azure. • Strong proficiency in Python, SQL, and ML frameworks (e.g., scikit-learn, TensorFlow, PyTorch). • Deep understanding of Azure services: Azure ML, Azure Data Factory, Azure Functions, Azure Kubernetes Service (AKS), and Azure DevOps. • Experience with MLOps, CI/CD, and infrastructure-as-code (e.g., Bicep, Terraform). • Familiarity with data governance, model interpretability, and responsible AI principles. Preferred Qualifications: • Azure Solutions Architect Expert or Azure AI Engineer Associate certification. • Experience with real-time inference and edge ML using Azure IoT and Azure Percept. • Background in regulated industries (e.g., finance, healthcare) is a plus. What We Offer: • Competitive salary and performance bonuses. • Flexible work arrangements and remote options. • Access to cutting-edge Azure technologies and enterprise-scale projects. • A collaborative, innovation-driven culture. Would you like this formatted as a downloadable PDF or tailored for a specific industry (e.g., finance, healthcare, retail)?