Pano AI aims to solve the critical problem of early wildfire detection and intelligence. Current methods rely on bystander reports, leading to delays in detection, verification, and response. This delay allows small fires to escalate into devastating infernos, posing a significant risk to communities due to amplified wildfire intensity driven by climate change.
Requirements
- 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.
- Publications in top-tier vision or ML conferences.
Responsibilities
- 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.
Other
- A PhD or MS in Computer Science, Electrical Engineering, Robotics, or related field, with a focus on computer vision, 3D perception, or geospatial AI.
- Excellent communication skills.
