Applied Scientist II, Grocery, Retail & In-Store Experience (GRAISE)
Core
Design, develop, and deploy machine learning and computer vision models to solve complex grocery-domain problems including product identification, shelf perception, and in-store scene understanding.
Role type
Applied Scientist (Computer Vision & Machine Learning)
Builds
Production-ready AI/ML systems for in-store grocery technologies (smart shopping carts, inventory intelligence, personalization)
Domain
Grocery & Retail / Computer Vision & Machine Learning
Deliverable
production ML models
Required skills
Machine learning, data mining, statistical algorithms, computer vision, deep learning, Java, C++, Python
Preferred skills
Large-scale data analysis, human-robotic interaction, data annotation workflows, model deployment optimization, technical documentation
Technologies
Java, C++, Python, Deep Learning frameworks
Responsibilities
Design and evaluate computer vision models for product identification and shelf perception; conduct exploratory data analysis to characterize domain challenges; own the model development lifecycle from experimentation to deployment; build and improve data pipelines and annotation workflows; communicate technical results to stakeholders; stay current with state-of-the-art research in multimodal learning.
Seniority
Mid-level, hands-on IC