SlipstreamJobs tracks this role from the company's public career site. Apply directly on the employer's site.
Pano AI is building AI-powered wildfire detection and intelligence systems to help fire professionals detect, respond to, and contain wildfires faster and more safely. The platform combines advanced hardware, software, artificial intelligence, satellite imagery, and real-time data from ultra-high-definition 360-degree cameras positioned at high vantage points across North America and Australia.
As a Senior Computer Vision Engineer, you will lead the design, development, optimization, and deployment of computer vision models and inference pipelines running on both cloud and edge devices. This is a hands-on technical leadership role with significant ownership of the edge AI and computer vision roadmap.
Key responsibilities include:
- Design and implement cloud/edge AI architectures for real-time computer vision applications
- Develop computer vision models for wildfire smoke detection, vegetation detection and classification, asset detection (power lines, utility poles, buildings, roads), scene understanding, semantic segmentation, and spatial reasoning
- Build lightweight detection, segmentation, classification, and temporal reasoning models for real-time inference
- Port and optimize deep learning models for ARM64, CUDA, TensorRT, ONNX, and NVIDIA Jetson platforms
- Build and optimize both cloud and edge inference pipelines for RGB, NIR, PTZ, and multi-camera systems
- Develop hybrid edge-cloud AI workflows balancing latency, bandwidth, and compute efficiency
- Improve inference latency, throughput, memory usage, and power efficiency
- Lead model compression efforts including quantization, pruning, and knowledge distillation
- Design deployment, monitoring, OTA update, and observability capabilities for edge AI systems
- Collaborate with AI researchers, software engineers, hardware engineers, data engineers, and product teams
- Mentor junior engineers and establish best practices for edge AI and computer vision development
Required qualifications: MS or PhD in Computer Science, Electrical Engineering, Robotics, or related field; 5+ years of industry experience in computer vision or machine learning; strong experience with PyTorch and modern deep learning architectures; experience deploying AI models to edge devices such as NVIDIA Jetson; strong understanding of CUDA, TensorRT, ONNX, model optimization, and inference acceleration; experience with object detection, semantic/instance segmentation, image classification, video understanding, or multi-object tracking.
