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Simbe Robotics is building an AI-powered operating system for physical retail, combining autonomous robots and multimodal computer vision to transform stores into sources of accurate, actionable intelligence. The company helps leading retailers improve shelf availability, price and promo execution, inventory accuracy, and store team productivity.
As a Customer Facing Applied AI Engineer, you will bridge computer vision, data infrastructure, product, customer success, and field operations. Your primary responsibilities include configuring, tuning, validating, and troubleshooting Simbe's AI pipelines in customer environments. You'll work directly with retailers to ensure they extract accurate and actionable insights from Simbe's Tally platform as quickly and reliably as possible.
This role sits at the intersection of technical depth and customer impact. You will own the end-to-end deployment experience for AI models in real-world retail settings, which means understanding both the technical nuances of computer vision systems and the practical constraints of retail operations. You'll collaborate with cross-functional teams including product, customer success, and field operations to identify issues, implement solutions, and continuously improve model performance.
Key responsibilities include: diagnosing and resolving issues with AI pipeline performance in production environments; tuning model parameters and configurations for specific customer store layouts and conditions; validating model outputs against ground truth data; documenting deployment procedures and best practices; and serving as a technical liaison between customers and internal engineering teams.
You should have strong fundamentals in machine learning, computer vision, or related fields, with hands-on experience deploying or working with ML systems in production. Experience with Python, data analysis, and debugging complex systems is essential. Familiarity with retail operations, robotics, or edge computing is a plus. You'll need excellent communication skills to translate technical concepts for non-technical stakeholders and the ability to thrive in a fast-paced, customer-focused environment.
