Architect - Machine Learning (Azure)

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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 system s 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

If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us !