Source Code Technologies LLC

Compensation

Full Description

AI/ML Engineer Location Mundelein IL Duration 3 months (Only Independent contractors) This is a Hybrid role (3 days onsite at Mundelein IL) As an AI Engineer 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 8 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.