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Owns quality analysis for annotated computer vision and machine learning data. Responsibilities include reviewing annotation queues, maintaining verdict taxonomies and guidelines, tracking performance by facility and equipment, detecting anomalies, conducting root cause analysis, reporting findings, improving annotation tools, and establishing quality processes for new programs. The role requires independent Python and SQL analysis, strong statistical reasoning, clear documentation, and collaboration with ML and engineering teams.

Own UX for operator tablet apps and an AI-driven dashboard, conduct field research in customer warehouses, prototype rapidly in Figma and AI tools, ship v2 quickly, and define the product's long-term design vision while collaborating tightly with product and engineering.

Own and architect the autonomy software stack for drone and vehicle-mounted systems, building perception, localization, and inventory scanning pipelines that run on embedded compute, improving scan accuracy, integrating sensors, and iterating with hardware and field teams to ensure reliable production deployments.

Lead design and implementation of perception, localization, and inventory scanning pipelines for vehicle-mounted embedded systems. Own architecture, improve scan accuracy and sensor integration, build scan-triggering and mapping software, and collaborate with hardware, ML, and field teams to diagnose and iterate on deployed systems in warehouse environments.

Own and evolve the robotics platform layer across drone and MHE products: ROS2/Zenoh communications, Docker-based deployments, diagnostics and observability tooling, deployment processes, and a roadmap to converge platforms while supporting multiple autonomy pods.

The role involves technical leadership in developing and integrating autonomous systems for logistics, including design, collaboration with teams, and mentoring.

Lead technical direction and hands-on implementation of enterprise-grade integrations, distributed services, and infrastructure. Improve scalability, reliability, security, observability, CI/CD, and APIs; mentor engineers; act as US-based customer technical contact to turn requirements into scoped production work.

Lead the Machine Learning strategy at Gather AI, focusing on computer vision, building teams, and enhancing ML systems for warehouse intelligence.

As a Principal ML Scientist, you will lead advancements in computer vision systems for warehouse inventory, overseeing the full ML lifecycle and collaborating with cross-functional teams.

Lead a hands-on hardware team to transition drone and MHE Vision hardware from prototype to scalable production. Define materials and design systems, manage vendors and contractors, implement documentation and change-review processes, and drive SWaP, shock, and vibration analysis to ensure rugged, manufacturable products for warehouse environments.