Note: The job is a remote job and is open to candidates in USA. Pano AI develops AI-powered wildfire detection and intelligence systems that combine hardware, software, computer vision, satellite imagery, and other data sources. The Senior AI/Computer Vision Engineer will lead the design, development, optimization, and deployment of AI models and inference pipelines across cloud and edge platforms, advancing wildfire detection, outdoor-scene understanding, and speech recognition for fire-related communications.
Responsibilities
- 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 (e.g., power lines, utility poles, buildings, roads) + Scene understanding and semantic segmentation + Spatial reasoning, including estimating distances and relationships between detected objects and nearby assets
- Develop speech recognition models for fire-related radio communications
- 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 that balance 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 closely 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
Skills
- • MS or PhD in Computer Science, Electrical Engineering, Robotics, or a 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, embedded GPUs, or similar platforms
- • Strong understanding of CUDA, TensorRT, ONNX, model optimization, and inference acceleration
- • Experience with one or more of the following: + Object detection + Semantic or instance segmentation + Image classification + Video understanding + Multi-object tracking + Depth estimation or 3D computer vision + Speech recognition
- • Strong Python and C++ programming skills
- • Experience with outdoor vision systems, autonomous systems, robotics, surveillance, remote sensing, or geospatial AI
- • Experience with PTZ camera systems
- • Experience with multi-camera calibration, localization, and distributed camera systems
- • Experience with spatial AI, scene understanding, or geometric computer vision
- • Experience estimating object distances or reasoning about spatial relationships using monocular, stereo, or multi-view imagery
- • Experience with MLOps and continuous learning pipelines
- • Familiarity with foundation vision models (e.g., DINOv2/DINOv3, SAM, Grounding DINO, Florence, or similar) is a plus
Benefits
- Regular full-time roles are eligible for equity.
- Benefits may include health coverage, retirement or pension contributions, and paid time off.
- Hybrid-remote environment
Company Overview
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