Top Artificial Intelligence Engineer Jobs in Chicago, IL

The role involves developing and implementing AI solutions, analyzing data for decision-making, and supporting project tasks in a fast-paced environment.

Develop and implement AI technologies and methodologies while mentoring others and maintaining high standards to drive project success. Analyze complex problems and foster a culture of innovation.

Lead the design and implementation of simulation-based validation strategies for autonomous systems, mentoring engineers and ensuring performance metrics are met.

Manage the development and validation of AI models, lead projects, provide strategic client interaction, and foster team improvement.

Collaborate to design, develop, and deploy AI solutions focusing on Generative AI and autonomous systems, requiring a strong ML engineering foundation.

Lead the design, training, and deployment of ML and LLM models, oversee cloud-native microservices, and mentor team members.

The AI Engineer - Manager will design AI solutions, lead teams, mentor staff, and drive strategic planning while delivering high-quality outcomes.

Lead development of production-grade generative AI applications, collaborate with cross-functional teams, and build tools for sales efficiency and customer engagement.

The Cloud Technical Support Engineer - Co-op will assist enterprise customers with integrating applications, diagnose issues, validate interoperability with third-party software, and work with R&D and development teams.

Lead Data & AI Engineer responsible for architecting and implementing intelligent analytics for a surveillance cloud platform, requiring strong skills in data pipelines, AI model management, and modern cloud technologies.

As a Staff Software Engineer, you will enhance developer productivity by establishing AI-driven tools, improving processes, and mentoring teams on AI integration and best practices.

Lead design and deployment of AI systems, develop agentic components, optimize performance, and mentor others in AI Engineering.

The Senior AI Engineer will design and deploy autonomous AI agents to optimize supply chain processes, lead AI initiatives, and enhance data integration and automation solutions.

The Staff AI Engineer will build and deploy advanced AI systems, focusing on Large Language Models and intelligent agents, to enhance user productivity and optimize customer journeys through intelligent automation.

Contribute to AI integration in developer workflows by implementing agents and servers; improve AI-generated changes and collaborate on experiments.

As a Lead AI Engineer, design and implement AI and machine learning models and pipelines to enhance healthcare outcomes and efficiency.

The AI Manager leads the development of AI/ML solutions, aligning them with business strategies. Responsibilities include project oversight, technical leadership, and ensuring compliance with ethical standards.

As an AI Engineer, you will develop AI solutions, drive Agile development, and collaborate across teams to enhance product features and user experiences.

The Data Engineer Co-op will work on web data feeds, utilize AI technologies and frameworks, and develop data pipelines.

Design and deploy AI/ML solutions using Azure, leading a team to enhance client value, collaborating across departments for effective implementation.

As a Staff AI Engineer, you will lead the design and delivery of AI solutions across business functions, focusing on speed and measurable outcomes. You will partner with various stakeholders, drive initiatives from concept to production, and shape technical direction while mentoring junior engineers.

As a Software Engineer on the AI Tools team, you'll improve productivity by integrating AI tools into workflows, developing software, and collaborating across teams.

Lead design and implementation of enterprise-grade AI systems, architect AI infrastructure, and drive technical strategy for AI-powered products primarily for military applications.

Lead the development of an AI framework for endpoint security, collaborate with teams, optimize solutions, and ensure model efficiency across various platforms.

Lead the design and deployment of AI applications, collaborating with teams to integrate LLM models and ensure performance metrics are met, while fostering continuous improvement.