Cloud ML Systems Architect

Role : Associate Architect - Machine Learning (Azure Cloud)

Experience : 6-13 Years

Location : Bangalore

Must have skills :

• Architect, develop, and deploy traditional machine learning solutions at scale.
• Lead end-to-end ML lifecycle including data preparation, feature engineering, model development, validation, deployment, and monitoring.
• Evaluate and optimize existing models using traditional ML techniques.
• Proven expertise in traditional ML algorithms (regression, decision trees, SVM, ensemble models, clustering, etc.)
• Strong coding skills in Python with experience in ML libraries such as scikit-learn, XGBoost, LightGBM, etc.
• Solid grasp of data preprocessing, feature selection, and statistical modeling.
• Deep understanding of ML pipeline orchestration and model lifecycle management.
• Ensure adherence to MLOps best practices and drive implementation on Azure cloud.
• Experience in Azure cloud services including Azure Machine Learning, Azure Data Factory, Blob Storage, and Azure DevOps.
• Leveraged Azure Cognitive Search and Azure OpenAI Service to build scalable and efficient knowledge retrieval systems, enabling real-time semantic search and contextual answer generation.
• Ability to design and review ML architecture and system integration strategies.
• Conducted proof-of-concept projects utilizing Azure’s AI ecosystem to explore agentic AI capabilities, including autonomous decision-making and task delegation.
• Designed and implemented RAG pipelines on Microsoft Azure, integrating large language models (LLMs) with domain-specific knowledge bases to enhance AI-driven information retrieval and response accuracy.
• Collaborate with data scientists, data engineers, and product stakeholders to convert business requirements into scalable ML models.
• Provide technical leadership, mentorship, and architecture-level guidance to project teams.
• Excellent problem-solving, communication, and stakeholder management skills.

Good to have skills :