City Detect harnesses AI and computer vision to revolutionize urban management. The Localization Engineer will lead the development and improvement of the localization module for data collection units, ensuring accurate vehicle localization and object detection.
Responsibilities:
- Lead development of sensor fusion algorithms and integration with object detection systems to accurately locate the vehicle and objects against municipal parcels, buildings, and infrastructure
- Take initiative to find performance gaps and implement long-term solutions for challenging issues caused by the complex relationship between remotely deployed software and a broad spread of hardware components
- Assess and develop approaches that improve localization and object detection performance (ie: usage records, log data, model efficiency, algorithm improvements) and methods to continuously evaluate the performance of these systems
- Contribute to the remote diagnostic and evaluation tools to determine customer unit performance
- Support and work collaboratively with AI and backend development teams to assess and improve localization and object detection performance
Requirements:
- 5+ years of professional experience in robotics, with a focus on localization or sensor fusion, and a broad understanding across multiple disciplines related to mobile data collection and refinement
- Experience designing and implementing state estimation or SLAM algorithms for real-world, real-time robotics frameworks (ie: ROS) in a production environment
- Strong programming skills in C/C++ and Python
- Comfort in building data-driven improvements from data-sparse remote diagnostics
- Experience with code quality and development processes for production code delivery - especially related to continuous, remote deployments
- Ability to work effectively both independently and collaboratively in a fast-moving team environment
- A masters or PhD in Robotics, Computer Science, Electrical Engineering or an applied engineering field
- Experience with AWS IoT or other remote system deployment and reporting mechanisms
- Experience with sparse remote data collection, development, and debugging, especially confidential or government data, by cars, trucks, or other low-contact vehicles
- Experience manipulating and integrating GIS municipality data (roads, parcels, infrastructure, etc) into low-resource systems
- Familiarity with camera calibration, GPS, or mapping ground-truth collection and evaluation