Teams at Shelfmark

Leads Shelfmark’s technical vision and organization, architecting an integrated industrial intelligence platform spanning computer vision, machine learning, hardware, firmware, edge computing, and software. Builds and scales a multidisciplinary engineering team, drives productization and deployment reliability, establishes monitoring and implementation infrastructure, and supports executive strategy, fundraising, and technical diligence. The role is hands-on and includes working with customers in manufacturing environments.

Develop, train, and optimize computer-vision and anomaly-detection models on imagery from live inspection lines. Deploy and profile models for low-latency edge inference, integrate with embedded systems, improve labeling and retraining workflows, diagnose production issues using real line data, and define ML standards and tooling for the team.

Develop and maintain embedded software for high-throughput line-scan camera systems and edge ML inference. Improve latency, reliability, deployment, observability, and data pipelines for on-prem devices, troubleshoot in the field, and collaborate with ML engineers to integrate and accelerate models.