Top Computer Vision Jobs in Austin, TX

The role involves developing perception systems for robotics, integrating them with planning and control systems, and evaluating performance under constraints.

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.

Lead teams building computer vision and machine learning for AI dash cameras, managing model lifecycle, coordinating with cross-functional teams, and driving AI product development.

As a Senior Machine Learning Engineer, you'll design and develop workflows utilizing vision-language models, manage data pipelines, and collaborate with multiple teams to enhance model accuracy and efficiency.

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.

The Perception Engineer will lead the design and deployment of the perception pipeline for detecting and tracking aerial threats using machine learning and computer vision technologies.

The Advanced Analytics Research Scientist will lead the development of vision-language-action systems for industrial applications, design multimodal learning systems, and evaluate system robustness. Collaboration with cross-functional teams is key for translating prototypes into deployable solutions.

Train and evaluate AI models for computer vision tasks, assess model accuracy, create training data annotations, and suggest improvements for visual data interpretation.

The Machine Learning Engineer will develop and deploy computer vision models, manage ML data infrastructure, and integrate systems for autonomous aerial platforms.

Develop and deploy computer vision and 3D reconstruction solutions: train and validate models (detection, segmentation), process pointclouds/meshes, implement SfM/photogrammetry and SLAM, integrate with microservices, APIs and cloud for production use.