Top AI & Machine Learning Jobs in Chicago, IL

Conduct applied AI research and develop automation, knowledge management, semantic search, retrieval, and reasoning systems. Build and evaluate proof-of-concepts, create frameworks for assessing AI risks and business impact, and collaborate with engineering teams to productionize successful concepts. The role explores agentic, causal, explainable, neuro-symbolic, and knowledge-enhanced AI, while contributing to publications and patents across financial services, fraud, risk, insurance, and marketing applications.

Designs, builds, and operates scalable AI platforms across multi-cloud and hybrid environments. Responsibilities include developing GenAI capabilities, RAG and agentic AI systems, observability, evaluations, guardrails, security, governance, and deployment automation. The role leads platform architecture, prototypes emerging technologies, ensures performance and reliability, partners with cross-functional teams, conducts design reviews, and mentors engineers.

Define and lead the AI enablement strategy, roadmap, and commercialization plan for TruIQ analytics products. Translate customer needs into product requirements, guide AI-enabled product development, establish evaluation and governance frameworks, and partner with Engineering, Data Science, Security, Compliance, and go-to-market teams. The role promotes responsible AI adoption in regulated environments, validates intelligent capabilities, builds customer trust, and mentors Product Managers on AI product practices.

Leads international data science and analytics product development, managing multiple teams of analytics managers and professionals. Oversees predictive modeling, analytical product delivery, talent development, budgeting, capacity planning, resource allocation, project management, reporting, operational policies, and stakeholder alignment. Requires management of 20+ employees, advanced analytics expertise, customer problem framing, global market knowledge, and formal presentation skills. International travel up to 50% is required.

Support model risk governance by maintaining policies, documentation, inventories, validation plans, training, and stakeholder communications. Develop statistical programs and analytical solutions using R, Python, SQL, Hive, Spark, and cloud platforms to analyze large datasets and support credit risk and business intelligence consulting engagements.