Python Developer

Analyze below job description and provide a set of technical questions for an interview As a Python / Computer Vision Developer, you will be responsible for the design, development, and implementation of innovative computer vision and AI-based solutions in the logistics and automation domain.

The primary role will izznclude developing and optimizing algorithms for object detection, recognition, tracking, and OCR/ANPR using Python and modern deep learning frameworks.

1. Responsibilities include designing, coding, testing, debugging, and documenting programs as well as supporting activities aligned with corporate AI/ML and systems architecture.
2. You will ensure support in analysis, model design, and system integration during all phases of solution delivery, including recommending the most effective approaches for deployment and scalability.
3. Your tasks will also include working on new research concepts, training pipelines, and AI model deployment across real-time video streams and edge/cloud environments.
4. Typically requires 5–7 years of applicable experience in Python, machine learning, and computer vision, with hands-on exposure to frameworks such as OpenCV, PyTorch, TensorFlow, or PaddleOCR/YOLO.

Skill Requirements:

1. Strong proficiency in Python (3.x) with focus on AI/ML and computer vision development.
2. Solid experience with OpenCV and at least one major deep learning framework: PyTorch, TensorFlow, Keras, or PaddlePaddle.
3. Hands-on experience with object detection models (YOLO, Faster R-CNN, SSD, etc.) and OCR frameworks (e.g., PaddleOCR, Tesseract).
4. Experience with real-time video/image processing (RTSP streams, edge devices, GPU acceleration).
5. Good knowledge of data preprocessing, augmentation, and annotation tools (LabelImg, PPOCRLabel, CVAT).
6. Familiarity with containerization (Docker), APIs, and cloud platforms (Azure, AWS, GCP) for model deployment.
7. Understanding of SQL/NoSQL databases for storing and retrieving processed data. Knowledge of Git, CI/CD pipelines, and Agile methodologies.

Skill – Nice to have

1. Experience with distributed systems and message queues (RabbitMQ, Kafka, gRPC).
2. Familiarity with Edge AI deployment (NVIDIA Jetson, Intel OpenVINO, TensorRT). Background in mathematics/statistics for AI optimization.
3. Exposure to C++ or .NET interop for hybrid solutions.
4. Experience in logistics, transportation, or industrial automation domain.