Senior Computer Vision Engineer

Role overview This role develops the computer vision systems behind AI dash cameras, fleet safety insights, and real-time video intelligence for a transportation platform. The work spans multi-camera calibration, object tracking, embedded AI deployment, and GPU inference optimization, turning high-resolution camera data into reliable perception systems for fleet operators. It is well suited to a senior engineer who can collaborate across embedded, firmware, backend, product, and operations teams to bring vision features into production.

Responsibilities - Design and develop computer vision systems for AI dash cameras and in-vehicle camera platforms - Build real-time perception pipelines for road-facing and cabin-facing camera streams - Develop models for object detection, multi-object tracking, driver monitoring, safety event detection, and road scene understanding - Perform multi-camera calibration, including intrinsic and extrinsic calibration - Apply stereo vision, multi-view geometry, 3D reconstruction, triangulation, and geometric projection methods - Build high-resolution video stream processing systems for real-time tracking at up to 60 FPS - Optimize computer vision models for embedded AI chip platforms and edge deployment, improving GPU inference latency, memory usage, and reliability - Implement Kalman filtering, temporal fusion, and multi-camera spatial fusion for real-world camera systems

Requirements - Strong proficiency in Python and computer vision development - Experience with PyTorch, OpenCV, TensorFlow, or similar ML and computer vision frameworks - Strong understanding of multi-camera systems, calibration, and geometric methods - Experience optimizing GPU inference and deploying models to constrained, edge environments

Nice to have - Background in real-time perception, tracking, or driver monitoring systems - Familiarity with embedded AI deployment and production CV pipelines

Benefits and work setup - Remote, full-time senior position on the Math & ML team