Data Scientist

Join our dynamic Data Science team as a Computer Vision and Natural Language Processing (CV-NLP) Engineer in Chennai. You will be instrumental in developing reusable tools and advanced machine learning models to address complex CV-NLP challenges. This includes tasks such as image classification, data extraction from documents, text classification, and summarization, working with diverse datasets including images, documents, and text.

Collaboration is key, and you will work closely with our DevOps and Data Engineering teams to build efficient Machine Learning (ML) pipelines. Your efforts will ensure the seamless integration and deployment of models into production environments, accelerating the model development lifecycle and enabling scalability for both training and production scoring. You will optimize model training throughput and response times by leveraging the latest technologies and techniques.

Required Experience and Expertise:

• A minimum of 1-3 years of hands-on experience in developing computer vision models and applications.
• Solid foundational knowledge in API Development and practical experience with Data Science and Machine Learning techniques.
• A strong understanding of the complete ML model development lifecycle, from development and training to testing, evaluation, and deployment.
• Proficiency in writing reusable code for various ML stages, including model training, testing, and deployment.
• Extensive experience in Python programming.
• Demonstrated success in developing ML solutions using frameworks like Scikit-learn, TensorFlow, Keras, and similar.
• Experience in addressing OCR challenges using pre-trained models and libraries such as Tesseract, Keras-OCR, EasyOCR, etc.
• Skilled in developing reusable APIs for integrating OCR capabilities into various applications.
• Familiarity with public cloud OCR services, including AWS Textract and GCP Vision.
• Experience integrating OCR solutions into production systems for extracting text from a wide range of images, PDFs, and other document types.
• A thorough understanding of CNN concepts and practical experience with deep learning models like YOLO.
• Ability to prototype, evaluate, and integrate the latest advancements in ML, particularly in the field of OCR.
• Experience with NLP tasks, such as Named Entity Recognition (NER) and text classification.
• Experience working with Large Language Models (LLMs).
• This role is ideal for individuals passionate about pushing the boundaries of CV-NLP, utilizing both established and cutting-edge methodologies to drive innovation.