Top AI & Machine Learning Jobs in Chicago, IL

Lead AI engineering teams to design, build, and deploy end-to-end AI solutions. Manage client relationships, plan and deliver projects, mentor staff, drive adoption of cloud-native microservices, CI/CD, vector databases and orchestration tools, and ensure high standards of quality, innovation, and compliance.

Analyzes workforce and healthcare data to identify trends, build predictive and machine learning models, and deliver actionable recommendations. Uses Python, Alteryx, and Power BI for analytics, visualization, and reporting. The role supports workforce strategy, employee engagement, organizational effectiveness, talent management, and healthcare cost insights. Responsibilities also include client collaboration, relationship management, team guidance, and applying risk adjustment and medical economics concepts to inform strategic decisions.

Leads the development and implementation of conversational and agentic AI solutions for contact centers and client interactions. Oversees user interaction engineering projects, designs interfaces with Dialogflow, Amazon Lex, Figma, Azure OpenAI, and ChatGPT, and conducts usability testing and user research. Advises clients, analyzes industry trends, validates data integrity and security, manages stakeholders, and coaches multidisciplinary teams to deliver innovative AI products and operational improvements.

Leads the design, development, deployment, and optimization of scalable AI and generative AI solutions. Translates business needs into secure, production-ready architectures; applies foundation models, NLP, retrieval, vector search, and agentic workflows; and implements MLOps and LLMOps practices. Manages project workstreams, evaluates solution performance, ensures security and compliance, collaborates with stakeholders, and coaches junior team members.

Lead design and delivery of scalable AI/ML systems: data wrangling, model training, deployment, and infrastructure. Manage teams, mentor staff, own project planning/budgeting, and collaborate with stakeholders to drive AI-driven business insights.

Lead one or more teams to design, build, and run cloud-native, AI- and data-intensive tax platforms. Provide technical and people leadership, guide architecture and implementation, drive agile and DevOps practices, mentor team members, collaborate cross-functionally, and transform complex tax challenges into scalable solutions.

Lead design and implementation of data architecture and scalable storage solutions, drive AI/GenAI thought leadership, oversee data governance and security, translate business requirements into technical plans, implement FastAPI endpoints, enhance LLMs through prompt engineering, and manage cross-functional teams to deliver advanced data and AI solutions.

Develop AI and data analytics solutions for AML and sanctions clients within PwC’s Risk & Regulatory practice. Responsibilities include Python-based data analysis, designing data architectures and pipelines, creating dashboards, interpreting complex datasets, engaging stakeholders, and delivering actionable insights and tailored client solutions. The role also involves client relationship building, problem-solving, continuous improvement, and contributing to strategic business outcomes.

Leads fraud and risk-focused data science initiatives, using Python and advanced analytics to generate strategic insights and improve business performance. Manages client engagements, data pipelines, project execution, and teams while mentoring staff and resolving stakeholder issues. Responsibilities include building data architectures, developing visualizations, improving processes, and maintaining professional, technical, and independence standards.

Design and implement AI-enabled integration solutions, cloud architectures, and enterprise technology platforms. Lead strategic planning, analyze business requirements, conduct feasibility studies, coach teams, manage stakeholders, and validate solutions with clients. Apply generative and agentic AI, IoT, sensor data, systems thinking, and enterprise architecture practices to solve complex business problems and drive innovation.