Machine Learning Engineer – Industrial Vision Systems (Junior to Mid-level) (ID105)

Key Responsibilities:

• Assist in building, curating, and annotating high-quality datasets for training computer vision models

• Train, evaluate, and fine-tune machine learning and deep learning models for specific vision applications

• Set up, configure, and manage camera and other hardware devices

• Contribute to the implementation of computer vision systems and multimodal AI agents for production use

Core Requirements:

• Good programming skills in Python

• Familiarity with at least one major deep learning framework, preferably PyTorch or TensorFlow

• Basic understanding of version control (Git)

• General awareness or basic knowledge of containerization tools like Docker

• Basic understanding of industrial communication protocols (e.g., OPC UA, Modbus TCP, or raw TCP/IP socket communication) and willingness to work with PLC/SCADA environments

Nice-to-Have:

• Computer Vision Specialties: Hands-on experience with specific tasks like anomaly detection, edge detection algorithms, or object detection models (e.g., YOLO variants).

• Camera Systems: Practical experience with camera calibration, handling real-time streams (OpenCV), or working with industrial/embedded camera hardware

• Model Optimization: Any experience in model deployment or optimization for production (e.g., ONNX, TensorRT)