Top Computer Vision Jobs in Seattle, WA

Design, train, and deploy custom object-detection models for retail; fine-tune and integrate vision-language models; optimize models for edge devices; build dataset and annotation pipelines; prototype research ideas; and provide technical leadership and mentoring for CV infrastructure and production ML systems.

The Director of Computer Vision will lead technical vision, research, and execution in developing scalable AI-driven computer vision solutions, managing teams, and enhancing performance metrics.

Develop and optimize computer-vision and deep-learning models (segmentation, depth) and end-to-end ML pipelines for perception. Own lifecycle from prototype to production deployment on edge and cloud, evaluate performance on large datasets, and collaborate with cross-functional teams to integrate perception into autonomous tractors.

Design, develop, and maintain Java-based cloud-native applications on GCP to support image capture, processing, storage, and distribution. Build REST APIs, image processing pipelines, and AI-enabled features (classification, OCR, redaction, similarity search). Ensure security, compliance, CI/CD, infrastructure-as-code, observability, and cross-functional collaboration.

Design and train foundation vision-language models that read entire CT studies end-to-end. Build custom PyTorch architectures and distributed training pipelines, run large-scale experiments, evaluate models for clinical safety, and move models through FDA submission to hospital deployment.

As a Computer Vision Applied Research Scientist, you'll design novel architectures for understanding construction drawings, conduct end-to-end experiments, and transition models to production. You'll collaborate with others to improve accuracy and address real-world issues in AI applications for construction.

Lead design and delivery of an egocentric video data product: capture rigs, edge processing, dataset pipelines, VLM-assisted annotation, and production-ready perception models (detection, tracking, segmentation, depth/3D reconstruction, and 6DoF pose estimation). Operate and scale warehouse capture programs and own model training, evaluation, optimization, and deployment.

Lead research, design, and production implementation of computer vision and ML solutions. Define architectures, run experiments, own model lifecycle (data, training, evaluation, deployment), optimize inference, set MLOps standards, mentor engineers, and collaborate with product and engineering teams to deliver production-quality CV features.

Design, implement, test, and maintain scalable C++ software for autonomous vehicle and perception systems. Work across full SDLC, support vehicle testing, simulation-based regression, data acquisition/analysis from remote vehicles, root-cause analysis, and mentor engineers while collaborating with ML researchers and cross-functional teams.

Lead design and implementation of computer vision systems for mapping, localization, image analysis, and 3D reconstruction on construction site data. Develop and optimize SLAM/SfM/VIO, deep learning perception models, and multi-modal approaches. Prototype, test, oversee datasets and collaborate with platform engineers to productionize scalable, robust solutions.