Top Hybrid Machine Learning Engineer Jobs in Chicago, IL

The Machine Learning Engineer will develop and optimize large-scale ML models, build low-latency inference pipelines, and collaborate with teams to enhance performance and automate ML processes.

Manage a team to assess model risks, build and validate machine learning models while leveraging advanced technologies and cross-functional collaboration.

This role involves leading analytics efforts using advanced machine learning techniques, handling large datasets, and creating actionable insights through data visualization at Caterpillar Inc.

As an Applied Machine Learning Engineer, you will develop AI and ML models to improve healthcare outcomes. Collaborate with teams to implement and optimize machine learning techniques and algorithms.

Develop scalable AI/ML software solutions, ensure quality and compliance, optimize performance, and collaborate on real-time systems. Manage data pipelines and models with a firm grasp of best practices.

The Staff Machine Learning Engineer will architect and optimize data infrastructure for multimodal AI models in oncology, focusing on data management and processing pipelines.

The ML Data Engineer develops and maintains machine learning pipelines and systems, collaborating with teams to optimize manufacturing processes through data-driven insights and predictive models.

The role involves designing and deploying strategies for congestion revenue rights, applying quantitative methods, and developing machine learning models.

The AI/ML Full Stack Engineer will design and maintain applications for predictive insights, develop data pipelines, implement ML models, and collaborate cross-functionally.

As a Senior Machine Learning Engineer, you will develop high-performance services, innovate AI/ML applications, design algorithms, and collaborate closely with teams to optimize ad systems.