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Role : Associate Architect - Machine Learning (Azure)

Experience : 8- 14 Years

Location: Bangalore

Job Summary

We are seeking an innovative and experienced Machine Learning Engineer at Architect level with a strong foundation in both traditional data science and modern Generative AI. The ideal candidate will lead the design, development, and deployment of high-impact, data-driven solutions on our Azure cloud infrastructure. You will be responsible for architecting complex systems, including multi-agent platforms and computer vision solutions, optimizing legacy models, and providing technical leadership to cross-functional teams to solve challenging business problems.

Must-Have Skills & Experience:

• Proven experience architecting, developing, and deploying traditional and deep learning solutions at scale, from concept to production

• Lead end-to-end ML lifecycle including data preparation, feature engineering, model development, validation, deployment, and monitoring

• Provide technical leadership, mentorship, and architecture-level guidance to project teams

• Demonstrated expertise in designing and implementing complex multi-agent systems

• Experience with agentic design patterns such as supervisor-worker and orchestrator-led group chats to automate intricate business processes (e.g., invoice processing, document automation)

• Experience with data augmentation techniques and human-in-the-loop annotation processes for large-scale model training

• Evaluate and optimize existing models using traditional ML techniques. Proven expertise in traditional ML algorithms (regression, decision trees, SVM, ensemble models, clustering, Random Forest, XGBoost)

• Deep understanding of ML pipeline orchestration and model lifecycle management with production-grade implementation experience

• Ensure adherence to MLOps best practices and drive implementation on Azure cloud

• Extensive experience in Azure cloud services including Azure Machine Learning, Azure Data Factory, Blob Storage, Azure DevOps, and Azure Container Apps

• 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

• 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

• Experience with evaluation, monitoring and observability frameworks for Agentic workflows.

• Experience designing fault-tolerant systems with robust error handling, fallback mechanisms, and state management for complex, multi-step AI workflows

• Ability to design and review ML architecture and system integration strategies with hands-on experience in production deployments

• Certifications in Azure AI Engineer or Azure Solutions Architect

• Excellent problem-solving, communication, and stakeholder management skills with experience presenting technical solutions to business stakeholders

Good to have skills:

• Collaboration skills with data scientists, data engineers, and product stakeholders to convert business requirements into scalable ML models

• Contributions to open-source projects