Hello! I'm Dharmik Mehta, a Senior AI Engineer with over 5.5 years of experience in Natural Language Processing (NLP) and Text Data Analysis. My journey in AI/ML has been driven by a passion for transforming complex data into meaningful insights and innovative solutions.
At the forefront of AI innovation, I specialize in Retrieval-Augmented Generation (RAG), Large Language Models (LLMs), and scalable GenAI solutions. My expertise spans across developing robust NLP algorithms, implementing end-to-end ML pipelines, and creating high-impact AI applications that bridge cutting-edge research with real-world challenges.
With a strong foundation in Information Technology and multiple industry certifications, I've successfully delivered solutions that leverage state-of-the-art AI/ML techniques. My work focuses on:
I'm passionate about pushing the boundaries of what's possible with AI and am always excited to collaborate on cutting-edge projects. Whether you're looking to discuss potential opportunities, share ideas about AI/ML, or explore innovative solutions, I'd love to connect!
Developed an advanced recommendation system using statistical machine learning models, focusing on a robust feature engineering process to extract relevant features for efficient model training. Managed the end-to-end machine learning lifecycle, from data ingestion to model training and deployment, while automating key processes. Developed Python scripts for data transformation and embedding management with large language models, implementing an application based on Retrieval-Augmented Generation (RAG) technology. Additionally, designed and exposed various APIs to facilitate model deployment and serving.
Proficiently developed machine learning models for various text analytics tasks, including document classification, medical named entity recognition (NER), and multilingual contract classification. Collected data from diverse sources through web scraping techniques and executed effective data preprocessing methods such as cleaning, transformation, and reduction. Demonstrated expertise in creating machine learning and deep learning models using transfer learning techniques with Keras and TensorFlow libraries. Successfully integrated these models into existing products. As part of the R&D team, contributed to research and exploration in machine learning methodologies and applications, driving innovation and enhancing overall capabilities.
Explored cutting-edge technologies, including machine learning, natural language processing (NLP), big data, Hadoop, Java 8, and Apache Solr. Acquired valuable knowledge in programming practices and coding standards while gaining exposure to a variety of tools and technologies. This internship provided a strong foundation in emerging technologies and their applications, enhancing technical skills and contributing to a deeper understanding of the field.
CGPA: 8.04
Percentage: 63.47
Percentage: 83.33