AI/ ML Architect Location: Northbrook, IL (100% onsite. No exceptions. Exceptional candidates can work 2 days a week from home) Duration: 6 Months Interviews: Immediate. Must-Have Skills: • Microsoft Azure ML Architecting Experience – 40% weightage • Microsoft Azure AI Architecting Experience – 40% weightage • Microsoft Azure DevOps Architecting Experience – 20% weightage As an AI Architect on the Data Science team, you will play a key role in productionizing machine learning models, building robust pipelines, and enhancing the overall AI platform. This role requires hands-on experience with Azure, Docker, and Azure Kubernetes Service (AKS), as well as strong knowledge of cloud-native MLOps best practices. Responsibilities • Design and implement scalable, cloud-native ML pipelines for production AI solutions. • Collaborate with data scientists to operationalize ML models from prototypes to production. • Manage deployment of ML models using Azure Machine Learning and AKS. • Develop, containerize, and orchestrate services using Docker and Kubernetes. • Optimize cloud data and compute architectures to ensure cost-effective and reliable deployments. • Implement robust monitoring, logging, and CI/CD practices to support AI operations (MLOps). • Work closely with enterprise cloud architects to align AI solutions with client’s infrastructure standards. • Contribute to the evolution of the best practices around AI/ML systems in production environments. Qualifications • Minimum 12 years of experience as a Data Scientist, with at least 3 years focused on machine learning engineering in cloud environments. • Proven experience deploying ML models in Azure, preferably with Azure Machine Learning, Docker, and AKS. • Hands-on experience building cloud-native pipelines for model training, scoring, and monitoring. • Familiarity with GenAI concepts and tools (experience operationalizing GenAI is a plus). • Proficiency in Python, SQL, and Linux-based development environments. • Strong understanding of MLOps principles, CI/CD pipelines, and production-grade APIs. • Effective communicator with strong problem-solving skills and ability to work across teams. Education • Bachelor’s degree in Computer Science, Electronic Engineering, Data Science, or a related field.