Top Machine Learning Engineer Jobs in Chicago, IL

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.

The Staff Machine Learning Engineer will define technical strategies, design ML models for document processing and risk assessment, and build scalable ML systems to protect Coinbase users' funds.

Lead the design and implementation of AI/ML models for risk and fraud detection at Coinbase. Collaborate with teams to develop scalable systems, mentor engineers, and ensure effective AI/ML solutions align with company goals.

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.

As a Staff Machine Learning Engineer, you will develop and maintain ML models for decision-making, optimize pipelines, and collaborate with a diverse engineering team.

The Machine Learning Engineer will develop and enhance ML models, design training pipelines, and analyze model performance. Responsibilities include maintaining inference services, collaborating with engineers for integration, and researching computer vision techniques.

As a Machine Learning Engineer Intern, you'll enhance model performance, develop production-grade tools, and automate workflows while receiving mentorship from experienced ML professionals.

As a Machine Learning Engineer, you will perform analysis on healthcare data, develop and deploy clinical machine learning models, and collaborate with various stakeholders.

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

Lead machine learning initiatives to enhance underwriting model accuracy. Design and implement advanced training strategies and optimize workflows. Mentor engineers and influence modeling strategy.

As a Staff Machine Learning Engineer, you will design AI products on Edge devices, optimize ML model performance, and work with large-scale datasets, collaborating across teams to deliver impactful solutions.

The Principal AI/ML Engineer will develop machine learning models for campaign optimization in AdTech, collaborating across engineering and product teams to enhance advertising capabilities.

Lead design and implementation of enterprise-grade AI systems, architect AI infrastructure, and drive technical strategy for AI-powered products primarily for military applications.

The role involves designing, developing, and deploying machine learning models for healthcare applications, collaborating with cross-functional teams, and optimizing model performance.

Develop and optimize machine learning models for data extraction from tax documents, collaborate on software integration, and mentor junior team members.

As a Senior Staff Machine Learning Engineer at Affirm, you will lead complex ML system design and implementation, mentor engineers, and drive innovative ML strategies for financial services.

Develop and productionize a next-gen Dispatch System, build predictive models, automate processes, and lead a small team in optimizing operations.

The Staff Full Stack Engineer will enhance machine learning workflows at Cruise by developing UX experiences, backend integrations, and overseeing system architecture and performance metrics.

Develop and productionize a next-gen Dispatch System, build ML models, automate processes, and collaborate with various teams while mentoring other engineers.

The Senior Applied Scientist II is responsible for designing and implementing ML models to optimize the supply chain, collaborating across teams, and driving data-driven decision-making.

As a Machine Learning Engineer, you'll enhance ML productivity, improve model deployment, and implement algorithms for credit decisioning systems.

As a Machine Learning Platform Engineer, you will partner with teams to establish data science environments, oversee analytic solutions, and lead complex projects while enhancing collaboration between technology and data science teams.

Lead the design, development, and deployment of machine learning applications, focusing on optimizing ML models and systems in a collaborative Agile environment.

Dandy seeks a Machine Learning Engineer to develop 3D computer vision models using SOTA methods, collaborate with product teams, and implement MLOps pipelines.

The role involves building computer vision models, researching deep learning methods, handling large datasets, and implementing MLOps best practices.