Top Computer Vision Jobs in Chicago, IL

As a Staff Software Engineer, you will lead the development of computer vision systems for sidewalk inspection, overseeing model lifecycle, system architecture, and mentoring while improving deployment practices.

Develop, train, and optimize computer vision and ML models (particularly video-based safety) using petabyte-scale camera and sensor data. Deploy and optimize models for backend and edge inference, collaborate with cross-functional teams, and translate customer needs into scalable ML/CV solutions.

The Senior Staff Machine Learning Scientist will lead research initiatives in computer vision and multimodal understanding, develop novel models, and translate research into practical applications while mentoring team members.

Develop learning-enabled imaging algorithms for 3D reconstruction and real-time adaptive acquisition of noisy synchrotron datasets; implement multimodal alignment and fusion of structural, chemical, and biological signals; collaborate with scientists across computational science, physics, biology, and environmental chemistry to guide experiments and analyze data.

Lead the development of AI-driven OCR and Image Recognition solutions, focusing on innovation, strategy, and team management in the retail sector.

Pre-sales Technical Solutions Architect focused on Physical AI: translates customer business problems into computer vision and robotics solutions, scopes and architects prototypes and POCs, enables sales teams, and develops practice content. Leads solution design across classical and modern vision toolkits, video and spatial intelligence, partners with ecosystem vendors, and builds business cases for deployments.

Pre-sales Technical Solutions Architect for Physical AI focusing on computer vision, video and spatial intelligence, and robotics. Engage customers and sales teams to qualify opportunities, design solutions, run proofs-of-concept, build business cases, collaborate with partners, and create technical content to develop the Physical AI practice.

Develop novel machine learning methods to enhance computer vision solutions, identify areas for innovation, and translate research into scalable production systems.

Join an R&D team to develop image-processing and computer-vision algorithms for 2D/3D scene segmentation, design experiments to detect long-tail model failures, and explore deep learning models and active learning methods to improve autonomous robotic vision systems.

The Machine Learning Engineer will develop editable visuals combining computer vision and machine learning, enabling chat-driven figure editing and leveraging biological understanding to produce accurate visuals.