AI Engineer - Text Document Extraction and Inference

We are seeking a Document Extraction and Inference Engineer with proficiency in traditional machine learning algorithms and rule-based NLP techniques. As the ideal candidate, you will possess a solid background in document processing, structured data extraction, and inference modeling through classical ML methods. Your primary responsibility will involve designing, implementing, and enhancing document extraction pipelines for diverse applications to ensure both accuracy and efficiency. Your key responsibilities will include developing and executing document parsing and structured data extraction techniques, leveraging OCR and pattern-based NLP for text extraction, refining rule-based and statistical models for document classification and entity recognition, creating feature engineering strategies to enhance inference accuracy, handling structured and semi-structured data such as PDFs, scanned documents, XML, and JSON, implementing knowledge-based inference models for decision-making purposes, collaborating with data engineers to construct scalable document processing pipelines, performing error analysis, and enhancing extraction accuracy through iterative refinements. Additionally, you will be required to stay abreast of the latest advancements in traditional NLP and document processing techniques. To qualify for this role, you must hold a Bachelor's or Master's degree in Computer Science, AI, Machine Learning, or a related field, accompanied by a minimum of 3 years of experience in document extraction and inference modeling. Proficiency in Python and ML libraries like Scikit-learn, NLTK, OpenCV, and Tesseract is essential, along with expertise in OCR technologies, regular expressions, and rule-based NLP. You should also have experience with SQL and database management for handling extracted data, knowledge of probabilistic models, optimization techniques, and statistical inference, familiarity with cloud-based document processing tools such as AWS Textract and Azure Form Recognizer, as well as strong analytical and problem-solving skills. Preferred qualifications for this role include experience in graph-based document analysis and knowledge graphs, knowledge of time series analysis for document-based forecasting, exposure to reinforcement learning for adaptive document processing, and an understanding of the credit/loan processing domain. This position is based in Chennai, India.,