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 role involves designing, building, and deploying computer vision models for vehicle damage detection, covering the entire ML lifecycle and collaborating across teams.

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.

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.