Computer Vision Applied Scientist, Pano AI

• A PhD or MS in Computer Science, Electrical Engineering, Robotics, or related field, with a focus on computer vision, 3D perception, or geospatial AI
• At least 2 years of industry experience in computer vision, foundational vision model, and multi-modal LLM
• Strong Python coding skills, especially with PyTorch

Desirable

• The Computer Vision Applied Scientist will be a part of the AI team that builds and deploys deep learning models to find, classify, locate, and track wildfires from cameras and satellites
• You will be working on computer vision, foundational vision model, multi-modal LLM, sensor fusion, 3D localization, and understanding scenes
• You'll work with platform engineers to create new software to help with this huge environmental challenge
• As a self-motivated and enthusiastic member of our team, you will work in an agile environment and balance developing critical new features with improving the core technical underpinnings of our system
• Developing smart geospatial algorithms for real-time awareness and predicting environmental risks from cameras and satellites
• Owning the deep learning models that understand environments, tell the difference between wildfires and other fires, pinpoint fires in 3D, and predict how they'll spread
• Constantly making our models and MLOps better, combining different sensor data, and using our existing domain knowledge to improve performance and real-time processing
• Working closely with the AI and platform teams to deliver awesome solutions for Pano's customers
• Showing off Pano AI's tech with solid real-world performance numbers