Top Computer Vision Jobs in Austin, TX

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

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.

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.

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.

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.

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.

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.