Architect - Machine Learning (Azure)
quantiphi · IN KA Bengaluru ·
- Category
- ML ai
- Experience
- 8+ years
quantiphi · IN KA Bengaluru ·
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!