Architect - Machine Learning (Azure)

Job description

While technology is the heart of our business, a global and diverse culture is the heart of our success. We love our people and we take pride in catering them to a culture built on transparency, diversity, integrity, learning and growth. If working in an environment that encourages you to innovate and excel, not just in professional but personal life, interests you- you would enjoy your career with Quantiphi! ****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 *If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us* *!*