2 months ago
Base Salary
$195k - $255k/yr
Responsibilities
- Design and implement cloud- and edge-based AI architectures for real-time computer vision applications.
- Develop models for wildfire smoke detection, vegetation detection and classification, asset detection, 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 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 using 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.
Requirements
- MS or PhD in Computer Science, Electrical Engineering, Robotics, or a related field.
- At least 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 NVIDIA Jetson, embedded GPUs, or similar edge platforms.
- Strong understanding of CUDA, TensorRT, ONNX, model optimization, and inference acceleration.
- Experience with object detection, semantic or instance segmentation, image classification, video understanding, multi-object tracking, depth estimation, or 3D computer vision.
- Strong Python and C++ programming skills.
- Preferred experience with outdoor vision systems, autonomous systems, robotics, surveillance, remote sensing, or geospatial AI.
- Preferred experience with PTZ camera systems, multi-camera calibration, localization, distributed camera systems, spatial AI, geometric computer vision, object-distance estimation, or monocular, stereo, or multi-view imagery.
- Experience with MLOps and continuous learning pipelines is preferred.
- Familiarity with foundation vision models such as DINOv2, DINOv3, SAM, Grounding DINO, or Florence is a plus.
Benefits
- Hybrid-remote work environment across North America and Australia.
- Benefits may include health coverage, retirement or pension contributions, and paid time off, depending on the employee's country of employment.
- Regular full-time employees are eligible for equity.
Categories
About Pano AI
Pano AI builds an early wildfire detection and intelligence platform that combines high‑vantage 360° cameras, satellite feeds, and AI software for real-time situational awareness. It sells an integrated hardware-and-software service to government agencies, utilities, insurers, and private landowners. Founded in 2019 and headquartered in San Francisco, the company operates in the United States, Australia, and Canada and reports monitoring more than 50 million acres.