Top Computer Vision Jobs in Chicago, IL

Work on vision-language model development and infrastructure: improve VLM understanding, OCR and function-calling workflows, fine-tuning recipes, evaluation and robustness, and optimize training/serving pipelines. Own end-to-end projects from experiments to production-ready code, collaborating on scale, cost, and reliability.

The role involves developing, adapting, and implementing machine learning algorithms for computer vision tasks in power grid analysis. Responsibilities include experimentation, error analysis, and project ownership.

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.

Annotate images and video for computer vision using bounding boxes, polygons, segmentation masks, and SKU-level labels. Audit model predictions, enforce annotation quality, identify hardware/software capture issues, and collaborate with ML, hardware, and product teams to validate fixes and improve data pipelines.

Lead and execute the production photogrammetry pipeline: design, build, train, and deploy 3D reconstruction systems at scale. Drive technical direction, optimize for speed and robustness, own observability and CI/CD, mentor engineers, integrate foundation 3D models and agentic AI tooling, and translate strategic goals into shipped work.

Early-stage founding-engineer hire to build and scale Safari AI's computer vision platform: lead product development, design data pipelines, deploy reliable cloud services, deliver incremental features, maintain production reliability, and ensure SDLC and security best practices while engaging enterprise customers.

The Computer Vision Researcher will develop and deploy advanced computer vision models, ensuring full lifecycle management, collaborating with teams, and driving research initiatives for player tracking.

As a Senior Research Scientist, you will advance research in deepfake detection and computer vision, develop scalable solutions, and collaborate with engineering teams while publishing your findings.

The Director of Computer Vision will lead technical vision, research, and execution in developing scalable AI-driven computer vision solutions, managing teams, and enhancing performance metrics.

The Computer Vision Engineer will develop and improve sports video models, conduct experiments, and collaborate with data teams to productionize models, focusing on player detection and tracking.