Principal Machine Learning Scientist

🕒 March 3

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Logo of Gather AI

Gather AI

11 - 50 employees

Founded 2018

🤖 Artificial Intelligence

🚗 Transport

🔧 Hardware

💰 $10M Series A on 2022-10

Artificial Intelligence • Transport • Hardware

Gather AI is a company specializing in automated inventory monitoring solutions using AI-powered drones. They enhance supply chain visibility and warehouse efficiency by offering real-time inventory intelligence, significantly reducing human error and inventory shrinkage. Their autonomous drones facilitate automated data collection and analysis, enabling fast and effective decision-making with increased productivity and accuracy. Gather AI serves industries such as 3PL, manufacturing, retail, and food and beverage, providing a modern approach to warehouse management through innovative technology.

📋 Description

• Advance core computer vision model performance (object detection, segmentation, OCR) for warehouse inventory scanning across drone and MHE Vision platforms • Own the full ML lifecycle from research and experiment design through production deployment and monitoring — applying rigorous ablation studies and SOTA methodology • Collaborate with the ML infrastructure team on model optimization and deployment across cloud and edge inference targets (ONNX, TensorRT, quantization) • Work with Operations and Product to understand customer needs and translate them into ML improvements with measurable business impact • Provide technical leadership and mentorship to the ML team, raising standards for experiment design, model evaluation, and production readiness • Explore next-generation perception capabilities, including embedded and on-prem inference optimization for new deployment targets

🎯 Requirements

• 10+ years of experience in machine learning or computer vision • Deep expertise in CNNs, object detection, image segmentation, and OCR using PyTorch (preferred) or TensorFlow • Strong Python proficiency and software engineering fundamentals; hands-on experience with OpenCV and GPU computing • Track record of delivering production ML systems at scale, including model training, evaluation, and deployment • MS or PhD in Computer Science, Machine Learning, Robotics, or a related field

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