07/11/2026 updated
100 % available
AI and ML Global Expert | NLP | LLM | Machine Learning Engineer
Gorakhpur, India
Worldwide
B.Tech, Pranveer Singh Institute of Technology, Kanpur (2014-2018)Artificial Intelligence and Machine Learning
Expertise in designing and deploying AI and ML solutions, including fine-tuning transformer-based models, building LLM-based automation systems, and developing enterprise-grade AI initiatives for payroll and legal process automation.
Natural Language Processing and Generative AI
Deep knowledge of Natural Language Processing, Large Language Models, Prompt Engineering, RAG Architectures, and Vector Databases, applied to document intelligence systems and business-driven AI solutions.
Programming and Data Science
Proficiency in Python, Django (REST APIs, scalable backend systems), Numpy, SQL, Statistics, Predictive Modelling, and Machine Learning, enabling robust data-driven application development.
Cloud and Development Technologies
Hands-on experience with AWS and GCP Cloud platforms, OpenCV, Chatbot Development, and Django-based backend architecture for scalable AI services.
Data Visualization and Analysis
Skills in Data Visualization, Market Basket Analysis, Recommendation Engines, and Fraud Detection to derive actionable business insights.
RAG-based Document Intelligence
Implementation of RAG-based document intelligence systems using vector search techniques for efficient information retrieval and processing.
Model Optimization and Performance
Optimization of model inference time and improvement of system performance through efficient pipeline structuring and fine-tuning of transformer models.
HTMX and Modern Frontend Integrations
Exposure to HTMX and modern frontend integration techniques to support full-stack AI application development.
Expertise in designing and deploying AI and ML solutions, including fine-tuning transformer-based models, building LLM-based automation systems, and developing enterprise-grade AI initiatives for payroll and legal process automation.
Natural Language Processing and Generative AI
Deep knowledge of Natural Language Processing, Large Language Models, Prompt Engineering, RAG Architectures, and Vector Databases, applied to document intelligence systems and business-driven AI solutions.
Programming and Data Science
Proficiency in Python, Django (REST APIs, scalable backend systems), Numpy, SQL, Statistics, Predictive Modelling, and Machine Learning, enabling robust data-driven application development.
Cloud and Development Technologies
Hands-on experience with AWS and GCP Cloud platforms, OpenCV, Chatbot Development, and Django-based backend architecture for scalable AI services.
Data Visualization and Analysis
Skills in Data Visualization, Market Basket Analysis, Recommendation Engines, and Fraud Detection to derive actionable business insights.
RAG-based Document Intelligence
Implementation of RAG-based document intelligence systems using vector search techniques for efficient information retrieval and processing.
Model Optimization and Performance
Optimization of model inference time and improvement of system performance through efficient pipeline structuring and fine-tuning of transformer models.
HTMX and Modern Frontend Integrations
Exposure to HTMX and modern frontend integration techniques to support full-stack AI application development.
Languages
EnglishFluent
Project history
Leading enterprise-grade AI/ML initiatives for payroll automation systems. Designing and deploying LLM-based automation solutions to streamline payroll workflows. Fine-tuning transformer-based models to reduce processing time and increase prediction accuracy. Implementing RAG-based document intelligence systems using vector search techniques. Building scalable backend AI services using Django-based architecture. Optimizing model inference time and improving system performance through efficient pipeline structuring. Collaborating with cross-functional global teams for AI system integration.
Designed and developed machine learning systems to automate legal processes. Analyzed data trends to create AI-driven legal insights. Monitored model accuracy and performance optimization.
Built machine learning models for automation and business intelligence. Collaborated with teams to integrate ML models into software applications. Researched new AI advancements for process improvements.