Responsibilities:• Collaborated with teams of product managers, designers, and developers to define and meet project specifications• Developed and maintained robust Python back-end code for various applications, ensuring scalability and performance• Designed, trained, and optimized DL models, LLMs and NLP applications, pushing the boundaries of AI to enhance user engagement and operational efficiency• Designed, trained, and optimized DL models, LLMs, and NLP applications to enhance user engagement and operational efficiency• Led R&D on new AI innovation for improving problem-solving capabilities and business outcomes• Debugging code, bug fixing, clearance from QA, documentation and third-party evaluationsAchievements:• Developed a Data Leak Prevention application that integrates OCR and utilise advance ML and Transformer-based algorithms to automate the detection of data breaches with high precision• Created an advanced semantic search application using LLM-based embeddings and Elasticsearch as a vector database• Implemented ETL pipelines with Elasticsearch to optimize data storage, search, and real-time analytics• Fine-tuned an LLM for a question-answer system, for internal decision-making by providing accurate answers to company-specific queries• Built and deployed RAG application on 80M docs, enhancing retrieval processes using LLama-2 LLM and Elasticsearch• Developed a web application integrating a 70-billion-parameter LLM in offline mode • Designed an automated data summarization tool by fine-tuning multiple LLMs• Developed an image classification application for validation of employee-submitted passport photos, ensuring adherence to company standards • Created a sentiment analysis application to analyze employee sentiments from extensive private company data• Perform real-time ship detection and classification in low visibility • Engineered multiple Python applications and APIs, dashboard creation, leveraging Elasticsearch and PostgreSQL