Top Hybrid Machine Learning Engineer Jobs in Chicago, IL

The role involves leading AI/ML initiatives, developing machine learning models, collaborating across teams, and operationalizing models in production.

Lead the design, development, and implementation of machine learning applications, focusing on architecture, model training, and deployment using emerging technologies.

The role involves developing machine learning models to detect fraud, collaborating with various teams, and leveraging advanced technologies for insights from complex data.

The role involves developing fraud protection models for Business Cards and Payments by analyzing data, collaborating with teams, and implementing machine learning solutions.

Lead AI & Analytics projects, build machine learning models for business decisions, collaborate with teams, and ensure effective communication of complex data insights.

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.

Join Braze as a Senior Software Engineer to enhance our ML platform, focusing on scalable AI solutions and robust coding practices. Collaborate across teams to leverage data infrastructure and implement ML models in production.

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 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.

Lead the design, training, and deployment of ML and LLM models, oversee cloud-native microservices, and mentor team members.

The Senior Machine Learning Engineer will develop and optimize voice-centric AI systems, manage ML lifecycle, and ensure high-quality conversational experiences in production environments.