AI Engineer, Computer Vision

What you'll do

• Train and evaluate visual localization models, including feature extraction and matching, image retrieval, pose regression, and scene-coordinate regression.
• Build and improve data pipelines and localization benchmarks, and run reproducible training experiments at scale.
• Support model deployment through export, inference optimization, and production monitoring; collaborate with research and field testing teams.

What they ask for

• Experience training deep learning models for computer vision in PyTorch.
• Foundational knowledge of visual localization, learned feature matching, image retrieval, pose estimation, SLAM, or structure-from-motion, including 3D geometry.
• Experience working with large image or 3D datasets and familiarity with GPU-based training.
• Strong Python skills.

Nice to have

• Publications or contributions in learned localization, visual place recognition, scene-coordinate regression, or vision foundation models; or experience with large-scale self-supervised or multi-view pretraining.
• Exposure to edge or mobile inference optimization, petabyte-scale spatial data, robotics or related fields, or production computer vision systems.

Pay

$165,600 - $221,000 per year (base salary)

Tools

PyTorch, Python, GPU, TensorRT, ONNX, CoreML

AI focus

Train and deploy visual models for centimeter-level localization, using camera imagery and spatial data to determine precise positions in the physical world.