Key Responsibilities:
- Design and implement robust algorithms for detecting and identifying on-screen graphics.
- Develop and fine-tune machine learning/computer vision models for pattern recognition, segmentation, and transformation of graphics in live video streams.Implement Optical Character Recognition (OCR) systems to extract text from graphicsEnsure real-time processing capabilities to handle live feeds without compromising quality or performance.
- Collaborate with the team to integrate models into production systems, ensuring scalability and reliability.
- Conduct research and experiment with state-of-the-art computer vision techniques and algorithms for video analysis,graphics replacement, and text translation.
- Work closely with product managers, engineers, and designers to ensure the product meets user and business needs.
Requirements:
Education: Bachelor's or Master's degree in Computer Science, Data Science, Computer Vision, or related field.
Experience:
- 3+ years of experience in computer vision or related fields.
- Hands-on experience with detecting patterns, segmenting visual components, or replacing graphical content in images or video.
Technical Skills:
- Proficiency in Python and/or C++ for implementing computer vision pipelines.
- Experience with frameworks such as TensorFlow, PyTorch, or OpenCV.
- Knowledge of OCR tools like Tesseract or advanced techniques for text recognition in images.
- Familiarity with translation APIs or NLP frameworks for language processing (e.g., Google Translate API, Hugging Face Transformers).
- Strong understanding of image/video processing, segmentation, and feature extraction.
Soft Skills:
- Strong problem-solving skills and attention to detail.
- Excellent communication and teamwork abilities.
Preferred Qualifications:
- Experience with video processing frameworks or real-time media pipelines.
- Understanding of multi-language support in OCR and translation systems.
- Knowledge of deep learning models for real-time graphics manipulation and enhancement.
- Background in broadcasting or live sports production is a plus