Job ResponsibilitiesData Acquisition & Backend Infrastructure (PostgreSQL & FastAPI)Design and implement a high-concurrency PostgreSQL database schema optimized for time-series data and rapid ingestion from multiple hardware sensors.Develop high-performance, asynchronous RESTful APIs using FastAPI to enable low-latency communication between control hardware and the data ecosystem.Create reliable drivers/interfaces to connect control hardware (sensors, PLCs, actuators) with the FastAPI backend, ensuring data integrity during high-frequency acquisition.Computer Vision Software Optimization (Python & C++ Integration)Design and refine a hybrid AI computer vision system that leverages C++ for performance-critical components (image processing, low-level memory management) and Python for high-level logic and model flexibility.Implement Python bindings for C++ libraries (using pybind11, Cython, or similar tools) to allow the AI pipeline to process real-time video streams with minimal overhead.Optimize OpenCV-based and deep learning pipelines (PyTorch or TensorFlow) to minimize latency and maximize throughput on edge devices or server-side hardware.Job RequirementsFresh Graduates WelcomeBachelor’s degree or higher in Computer Science, Computer Engineering, Electrical Engineering, or a related field Strong proficiency in Python and C++Solid experience with AI/deep learning frameworks (PyTorch and/or TensorFlow)Practical experience with OpenCV in object detection, segmentation, and/or tracking tasksPreferred: Experience with Docker and Linux environments for containerizing high-performance backend and AI workloadsGood team player with strong self-motivation and problem-solving skillsKnowledge of PostgreSQL optimization, familiarity with hardware communication protocols (e.g., Modbus, CAN, SPI, MQTT), experience with data acquisition (DAQ) hardware will be the advantageous
