Top Machine Learning Jobs in Chicago, IL

Lead the technical vision for Upstart's ML and simulations platform, modernizing infrastructure and mentoring a team while collaborating cross-functionally.

Manage and lead a team of Analysts, focusing on marketing measurement, optimizations, and utilizing machine learning to enhance campaign performance for clients.

The Senior Machine Learning Engineer will evaluate and apply advanced ML models, integrate with company infrastructure, and support data pipeline orchestration while focusing on autonomous vehicle technology.

Lead centralized Machine Learning efforts at Affirm, managing model development lifecycles, fostering AI adoption, and overseeing a team of ML professionals to enhance business outcomes.

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 define technical strategies, design ML models for document processing and risk assessment, and build scalable ML systems to protect Coinbase users' funds.

The Staff Machine Learning Engineer will utilize AI models, mentor team members, and enhance automation solutions across Coinbase's operations, focusing on machine learning to solve complex challenges.

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

Drive the strategic vision for machine learning initiatives, lead development of ML models, oversee data analysis, deploy ML solutions, and mentor junior staff.

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.

The role involves advanced data analysis, designing data solutions, developing machine learning models, collaborating across teams, and providing strategic insights to improve business decisions.

The Principal ML Engineer will establish personalization strategies, solve complex ML challenges, design advanced ML solutions, and mentor junior engineers.

The Principal ML Engineer will define and implement ML personalization strategies, architect scalable systems, mentor engineers, and contribute to the ML community while focusing on innovative, privacy-preserving solutions.

Lead ML strategy and architecture focused on personalization, solve complex challenges, mentor engineers, and represent the company in the ML community.

Lead the technical vision for personalization at Launch Potato, solving complex ML challenges and driving alignment across teams using advanced ML techniques.

The Principal Machine Learning Engineer will design ML architecture, solve technical challenges, mentor other engineers, and lead initiatives across the company.

Lead a team of ML engineers to develop advanced personalization and optimization systems while mentoring, managing technical projects, and collaborating across departments.

Lead a team of ML engineers to build personalization systems, focusing on architecture, model quality, and team mentoring while coding 50% of the time.

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.

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

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.

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 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.

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