Top Machine Learning Jobs in Chicago, IL

As a Principal Associate in Data Science, you'll develop modeling approaches, collaborate on cross-functional teams, and apply explainability techniques to improve credit decisioning at Capital One.

The Staff Research Scientist will conduct AI research, innovate in LLM and information retrieval, and collaborate with research teams.

Lead technical vision and execution for enterprise-scale AI, automation, and data initiatives. Architect scalable, secure AI systems and data pipelines, mentor engineers, drive cross-functional alignment, and deliver high-impact production solutions that improve productivity and business outcomes.

Lead Data Scientist partners with business leaders to identify opportunities, design, develop, and deploy advanced analytics and ML solutions. Responsibilities include data preparation, modeling, feature engineering, delivering insights and visualizations, establishing standards, and directing associate data scientists, contractors, and consultants to produce measurable business value.

The Research Engineer will collaborate with scientists to develop and validate machine learning models for speech technologies, manage scalable training systems, and design tools for accessibility to non-technical users.

Lead design, development, and productionization of ML and LLM/NLP systems. Own feature engineering, model evaluation, monitoring, and bias analysis. Partner with Product and Engineering to drive operational impact and act as senior technical owner and reviewer for data science work.

Lead AI/machine learning innovations and advanced analytics for new vehicles. Develop statistical models for pricing and valuation, guiding experiments and communicating insights.

Design and build ML infrastructure, influence data access and model deployment, partner with researchers to optimize ML models for trading, and mentor engineers.

Lead the development of fraud prediction models using machine learning, collaborating across teams to build, scale, and monitor models in production.

Lead a team of ML engineers to develop fraud detection models, defining strategies, driving model evolution, and ensuring effective integration with cross-functional teams.

As a Lead Machine Learning Engineer, you will design, implement, and optimize ML systems, collaborate with teams, and ensure model performance.

Conduct ML and deep learning research to build, test, and deploy predictive models for trading. Collaborate with traders, researchers, and engineers to engineer features, preprocess data, prototype algorithms, and improve production research tooling to enhance trading performance.

Lead development and deployment of ML models for trading, drive research and prototyping, oversee data and feature engineering, mentor researchers, and build scalable ML research infrastructure.

Design, build, deploy, and maintain production ML models and data pipelines at scale. Collaborate with product and data science teams, apply ML best practices, monitor model performance, and use cloud and CI/CD tooling to ensure resilient, governed, and explainable ML systems.

Design, build, and scale multi-cloud analytics and AI/ML platforms. Lead cloud-native data pipelines, storage, streaming, governance, and security while providing technical leadership, automation, and DevOps for platform reliability and performance.

As a Data Scientist, you will develop algorithms, collaborate on product requirements, and communicate data-driven insights, while enhancing product offerings and delivering actionable insights.

The Senior Data Scientist will analyze data to drive product strategy, optimize performance, and support product launches, collaborating with cross-functional teams.

The AI Platform Engineer III will lead AI and data platform solutions, mentor team members, and design robust architectures for data products, collaborating with business partners to solve complex problems.

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 technical direction of a computer vision platform for sidewalk inspection. Responsibilities include managing ML models, improving data pipelines, and architecting systems for terabytes of geospatial data.

The AI Solutions Lead will identify, develop, and implement AI applications, collaborate with teams and clients, design prototypes, and support deployments, requiring hands-on development and innovation.

The Senior Machine Learning Engineer will design, build, and deploy AI agents at scale, enhancing Dropbox Dash's search and organization features. Requires extensive ML experience and proficiency in Python and ML libraries.

The Director of CX AI will develop and execute the AI roadmap for customer experience, evaluate tools, modernize workflows, and ensure responsible AI use.

The Lead Engineer will oversee AI agent development, ensuring quality and compliance, and collaborate with business teams on AI projects.

As an AI Consultant, you will bridge clients and engineering teams, translating business needs into technical requirements and managing client communications.