Mobile Application Developer
BridgeView
- Ort
- Golden, US
- Arbetsplats
- På plats
- Anställningsform
- Heltid
- Lön
- $130k–$170k
- Publicerat
- 5 dagar sedan
- Källa
- DevITJobs
Requirements:
- Strong Python programming skills, particularly for machine-learning training pipelines.
- Experience with computer vision frameworks such as OpenCV, PyTorch, or TensorFlow.
- Demonstrated ability to deploy machine-learning models to mobile or edge devices.
- Proficiency with at least one mobile development framework, such as Flutter, React Native, Swift, or Kotlin.
- Familiarity with image annotation, data augmentation, model optimization, and inference performance.
- Ability to work independently, research technical challenges, and resolve deployment issues.
- Knowledge of hardware acceleration technologies, including Apple Neural Engine or GPU acceleration, preferred.
- Experience with YOLO-based object detection architectures is a plus.
Responsibilities:
- Develop a mobile application prototype that uses on-device AI to count stacked warehouse supplies.
- Train and refine custom object detection models using YOLOv8, YOLOv11, YOLO-NAS, YOLOX, or similar frameworks.
- Set up an image annotation workflow with Roboflow, CVAT, or similar tools to label approximately 300–500 inventory images.
- Optimize and deploy trained models with CoreML or TensorFlow Lite for offline mobile inference.
- Build a mobile interface that displays real-time object counts, bounding boxes, and detection overlays from camera feeds or uploaded images.
- Test and improve model accuracy across different lighting conditions, camera angles, and warehouse environments.
- Collaborate with project stakeholders to refine functionality and troubleshoot deployment issues.
Technologies:
- AI
- Computer Vision
- Flutter
- Hardware
- Kotlin
- Mobile
- Model Training
- PyTorch
- Python
- React
- React Native
- Swift
- TensorFlow
- opencv
- Machine Learning
- UX UI Design
More
We are seeking a Mobile Application Developer to build a functional prototype that uses on-device artificial intelligence to identify and count stacked warehouse inventory. The role combines custom object detection model training, mobile application development, and edge AI deployment. Frequent onsite collaboration and hands-on testing are required.
last updated 43 week of 2026