Top Senior Machine Learning Jobs in Chicago, IL

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.

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.

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 Staff Machine Learning Engineer will lead model development to detect fraud, manage financial risks, and mentor other engineers. Responsibilities include system design, architecture, and applying AI/ML methodologies in a cross-team capacity.

The Senior Machine Learning Platform Engineer will develop ML models, mentor engineers, optimize systems, and enhance ML infrastructure at Coinbase.

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.

Lead the design and implementation of AI/ML models to enhance risk and fraud management. Collaborate across teams to prevent fraud and account takeovers, mentoring senior engineers in technical excellence.

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 design AI products on Edge devices, optimize ML model performance, and work with large-scale datasets, collaborating across teams to deliver impactful solutions.

The role involves building AI technologies for customer service, developing ML systems, and collaborating with cross-functional teams to enhance user experiences.

The Senior Machine Learning Engineer will design, prototype, build AI systems, evaluate ML models, and improve Vectara's AI Agents with a focus on reliability and performance.

As a Senior Machine Learning Engineer on the Perception Team, you will define technology direction, architect solutions for autonomous vehicles, collaborate with team members, and mentor junior engineers, contributing to high-stakes projects in autonomous driving.

The ML Engineer will work on RL frameworks, develop synthetic data engines, and maintain performance evaluations for a closed-loop drug discovery platform.

The role involves building a recommendation engine, designing ML systems, making data-driven decisions, and collaborating with leadership to enhance user experiences.

Develop and optimize machine learning models and workflows to enhance insurance processes. Collaborate on model integration, monitoring, and improvement while driving innovation in modeling techniques.

Research Engineer will conduct Machine Learning research to enhance localization and global entertainment, focusing on ASR, Speaker Diarization, and Audio Understanding.

Lead the ML and AI engineering team, strategizing and implementing AI solutions for business growth, mentoring staff, and collaborating across departments.

Build and optimize machine learning models for 3D dental applications, research state-of-the-art methods, and implement MLOps best practices.

Lead the design, execution, and analysis of machine learning-driven product experiments to optimize ordering systems. Collaborate with stakeholders and mentor teams.

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

As a Senior Machine Learning Engineer, you will develop scalable ML solutions, collaborate with teams, optimize models, and implement best practices for deployments and infrastructures.

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.

The Senior Machine Learning Engineer will develop ML APIs, build data pipelines, and collaborate across teams to enhance ML models and applications.

As a Senior Machine Learning Engineer, you will design ML infrastructure, lead zero-to-one initiatives, collaborate on projects, and enhance scalability in the development of ML applications.