Data Scientist/Computer Vision Engineer

Remote Full-time
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

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