Consultation & Setting Up Google Cloud VM for Label Studio via Dockers + SAM 2 Video & Google Drive

Role: Full-Stack Systems & Edge AI Engineer We are a Singapore-based startup building cutting-edge computer vision solutions for the food industry. We are seeking a hands-on, end-to-end engineer to take ownership of our pipeline—from edge-side data capture to cloud-based model training and deployment. What You’ll Do: Edge Pipeline Development: Architect and maintain low-latency inference pipelines using YOLO, BoT-SORT, and OpenCV to run reliably on edge hardware. Cloud Infrastructure: Manage data flows between edge devices and GCP using rClone and Google Cloud Storage. Data Ops: Streamline our annotation workflow using Label Studio (Dockerized) and curate high-quality datasets with FiftyOne. Model Lifecycle: Leverage SAM 2 for advanced segmentation tasks and manage the full cycle of training, evaluation, and edge deployment. System Integration: Develop robust, asynchronous backend services using FastAPI to connect our edge systems to the cloud. Who You Are: A pragmatic problem-solver who enjoys moving from prototype to production. Experienced in navigating the trade-offs between edge hardware constraints and model performance. Passionate about building scalable AI systems that solve real-world problems in the food industry.