Full-Time Computer Vision Applied Scientist

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.

• 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.

• Experience working with geospatial data, GIS, or remote sensing.
• Experience working with cloud systems.
• Excellent communication skills.
• Publications in top-tier vision or ML conferences.

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