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!
