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Key Responsibilities:
Be a part of a dynamic Data Science team in developing scalable, reusable tools and capabilities to advance machine learning models, specializing in computer vision, natural language processing, API development and Product building.
Drive innovative solutions for complex CV-NLP challenges, including tasks like image classification, data extraction, text classification, and summarization, leveraging a diverse set of data inputs such as images, documents, and text.
Collaborate with cross-functional teams, including DevOps and Data Engineering, to design and implement efficient ML pipelines that facilitate seamless model integration and deployment in production environments.
Spearhead the optimization of the model development lifecycle, focusing on scalability for training and production scoring to manage significant data volumes and user traffic. Implement cutting-edge technologies and techniques to enhance model training throughput and response times.
Required Experience & Expertise:
3+ years of experience in developing computer vision & NLP models and applications.
Extensive knowledge and experience in Data Science and Machine Learning techniques, with a proven track record in leading and executing complex projects.
Deep understanding of the entire ML model development lifecycle, including design, development, training, testing/evaluation, and deployment, with the ability to guide best practices.
Expertise in writing high-quality, reusable code for various stages of model development, including training, testing, and deployment.
Advanced proficiency in Python programming, with extensive experience in ML frameworks such as Scikit-learn, TensorFlow, and Keras and API development frameworks such as Django, Fast API.
Demonstrated success in overcoming OCR challenges using advanced methodologies and libraries like Tesseract, Keras-OCR, EasyOCR, etc.
Proven experience in architecting reusable APIs to integrate OCR capabilities across diverse applications and use cases.
Proficiency with public cloud OCR services like AWS Textract, GCP Vision, and Document AI.
History of integrating OCR solutions into production systems for efficient text extraction from various media, including images and PDFs.
Comprehensive understanding of convolutional neural networks (CNNs) and hands-on experience with deep learning models, such as YOLO, DETR.
Strong capability to prototype, evaluate, and implement state-of-the-art ML advancements, particularly in OCR and CV-NLP.
Extensive experience in NLP tasks, such as Named Entity Recognition (NER), text classification, and on fine tuning of Large Language Models (LLMs).
This senior role is tailored for visionary professionals eager to push the boundaries of CV-NLP and drive impactful data-driven innovations using both well-established methods and the latest technological advancements.
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