Simbe Robotics
Customer Facing Applied AI Engineer, Retail Perception
About this role
Simbe seeks a Principal or Staff Robotics Perception Engineer to bridge computer vision and robot software teams, translating perception models into production robotic behavior for autonomous retail robots. You'll enhance navigation, localization, and store intelligence while working with multimodal vision and robotics systems.
What you'll do
- Own the pipeline from perception models and sensor data to deployed robotic behavior in retail environments
- Improve autonomous robot navigation, localization, and calibration in dynamic store settings
- Collaborate between Computer Vision and Robot Software teams to integrate vision capabilities
- Develop and optimize perception systems for retail-specific tasks like shelf availability and promo detection
- Translate computer vision outputs into actionable robotic control and decision-making
- Ensure production reliability and accuracy of perception-driven autonomy features
What they're looking for
- Robotics perception and sensor fusion
- Computer vision (multimodal approaches preferred)
- Robot software architecture and ROS or similar frameworks
- Localization and SLAM techniques
- Machine learning model optimization for deployment
- Calibration and sensor integration
- Python or C++ for robotics
- Production systems debugging and reliability
Opens the application — the Jobs AI extension fills it for you. Set up autofill
Opens the official application on the employer’s site. No login required.
Simbe Robotics
Simbe Robotics builds Tally, an autonomous retail robot platform that collects inventory and shelf data for retail stores. The company is hiring software engineers, QA/test engineers, deployment specialists, and enterprise solutions engineers to develop, test, deploy, and support its robotics technology stack and customer integrations.
- Website
- simbe.com
Likely interview questions
- Walk us through a project where you bridged perception models and robotic control—what were the key challenges?
- How have you approached sensor calibration and fusion when deploying robots in unstructured, changing environments?