Application Developer

QTI is partnering with a growing organization seeking an experienced App Developer to help build a mobile application utilizing artificial intelligence and computer vision technology. This is an exciting opportunity to develop a real-world AI-driven solution from concept through prototype. The ideal candidate will have experience training and deploying object detection models and will enjoy working in a collaborative environment where they can directly influence the success of the project. This project is expected to last 4-8+ weeks , with potential for additional projects and longer-term opportunities based on project success. Schedule: Monday-Friday, approximately 9:00 AM-5:00 PM. Hybrid work environment with a mix of onsite collaboration and remote development work. Location: Candidates must be based in Southern Wisconsin and available for frequent onsite collaboration and prototype testing in the Fort Atkinson area. Compensation: Starting at $30+/hour, based on experience. Responsibilities: Develop a functional prototype of a mobile application utilizing artificial intelligence and computer vision technology. Train and deploy custom object detection models using frameworks such as YOLOv8, YOLOv11, YOLO-NAS, YOLOX, or similar technologies. Build and maintain machine learning training pipelines. Prepare and manage image annotation workflows using tools such as Roboflow, CVAT, or similar platforms. Label and organize image datasets to support model training and testing. Optimize machine learning models for deployment on mobile and edge devices. Export and deploy models using technologies such as CoreML, TensorFlow Lite, or similar frameworks. Develop a clean and intuitive user interface that displays real-time object detection results. Participate in prototype development, testing, troubleshooting, and continuous improvement. Research and resolve deployment and application issues independently. Qualifications: Demonstrated experience developing and deploying computer vision or object detection solutions. Hands-on experience with YOLO architecture or similar object detection frameworks. Experience with OpenCV, PyTorch, TensorFlow, or similar technologies. Experience deploying machine learning models to mobile or edge devices. Familiarity with Flutter, React Native, Swift, Kotlin, or similar mobile development platforms. Strong problem-solving and troubleshooting abilities. Authorization to work in the United States. Ability to provide a portfolio, GitHub repository, or examples of successful object detection projects. #J-18808-Ljbffr