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Top Machine Learning Jobs in Chicago, IL
The Senior Machine Learning Engineer at Capital One will design and implement machine learning models and systems, collaborate with cross-functional teams, optimize ML applications, and ensure high performance and availability of deployment. Responsibilities include data pipeline construction, ML model monitoring, and leveraging cloud technologies.
As a Data Analytics Senior Consultant, you will lead projects to create automated scorecards and scenario analysis tools for underwriting strategies in a commercial insurance context. The role requires strong analytical and technical skills to derive insights from data analytics solutions that support decision-making across the organization, collaborating closely with senior leadership and other teams.
As an Applied AI Scientist, you'll develop advanced algorithms, execute statistical techniques on large datasets, evaluate emerging datasets, and contribute to the firm's thought leadership through research and publication.
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As an AI Researcher at DRW, you will develop and test AI models and algorithms, construct data pipelines, evaluate model performance, and collaborate closely with your team. You will also stay informed on the latest AI techniques and contribute to improving research processes, all while receiving mentorship and participating in a robust training program.
As a Software Engineer in Machine Learning Platform & Operations, you will support the development and deployment of machine learning models, build self-service components for the ML platform, and enhance cloud infrastructure solutions. You'll collaborate with various teams to ensure effective machine learning system development.
The Machine Learning Engineer will develop large-scale distributed training pipelines, build low-latency inference systems, and optimize model performance using GPU acceleration. Collaborating with researchers, the role involves enhancing ML frameworks and automating experiments while working within high-pressure trading environments.
As an Application Engineer, you will oversee design and implementation of assigned products, manage risks, analyze and deploy new user stories, guide junior engineers, and enforce IT standards. Collaboration with various stakeholders is crucial for achieving team commitments and ensuring high reliability of solutions.
The Staff ML Infrastructure Engineer will be responsible for defining the technical vision and architecture for Thumbtack's machine learning infrastructure, leading cross-functional teams, and establishing best practices. The role includes mentoring, strategic decision-making, and aligning ML capabilities with business goals, all to support the company's AI-first approach.
As a Principal Software Engineer in AI/ML Integrations, you will design, develop, and deploy AI & ML integration pipelines within the elluminate platform. Collaborate with data science teams to streamline data management and analytics for clinical trials, while ensuring scalability, performance, and security. Contribute to architectural decisions and mentor junior engineers in a collaborative environment.
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The Senior Machine Learning Engineer at Wasabi will advance AI technologies, develop computer vision algorithms, and implement NLP model fine-tuning. This role involves collaborating with teams for seamless machine learning integration, conducting testing, debugging, and ensuring reliable system operations.
Top Companies in Chicago, IL Hiring Data + Analytics Roles
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