<p>Employee Type: Regular TS/SCI Clearance Bachelor's degree in Computer Science, Data Science, Mathematics, Statistics, Engineering, or a related field. 3-5 years of experience in machine learning, deep learning, or AI system development. Experience in MLOps, containerization (e.g., Docker, Kubernetes), and CI/CD pipelines. Proficiency in designing, developing, and deploying machine learning models. Advanced knowledge in data preprocessing, including handling large datasets in cloud environments. Experience in developing custom AI APIs and integrating them into enterprise applications. Strong knowledge of programming languages for Machine Learning (Python, R, or similar). Good understanding of AI cloud tools and capabilities. Familiarity with Responsible AI (RAI) policies and development of metrics, measurements, and evaluation methods for AI. Knowledge of distributed computing frameworks (e.g., Apache Spark) Familiarity with version control systems (e.g., Git) This position is contingent on funding and may not be filled immediately. However, this position is representative of positions within CACI that are consistently available. Individuals who apply may also be considered for other positions at CACI. What You Can Expect: Design, develop, and deploy machine learning models and manage pipelines using tools such as Azure ML, Kubeflow, or MLflow. Implement and manage MLOps practices, including containerization (e.g., Docker, Kubernetes) and CI/CD pipelines. Handle large datasets in cloud environments, performing advanced data preprocessing. Develop custom AI APIs and integrate them into enterprise applications. Ensure adherence to Responsible AI (RAI) policies and develop metrics, measurements, and evaluation methods for emerging and existing AI areas. Collaborate with cross-functional teams to identify opportunities for AI/ML integration and improvement. AI Engineer Associate (AI-102) Microsoft Certified: Data Scientist Associate</p>