Professional Overview
Results-driven Artificial Intelligence and Machine Learning Engineer with hands-on experience designing and deploying intelligent AI solutions using Machine Learning, Deep Learning, Natural Language Processing, and Generative AI. Proficient in Python, TensorFlow, PyTorch, Scikit-learn, and modern LLM frameworks, with practical expertise in Retrieva
Experience
AI Expertise
Skills
Employment Type
Description of Responsibilities
- Built and deployed Retrieval-Augmented Generation (RAG) applications .
- Developed AI agents using Python, LangChain, MCP, and OpenAI APIs.
- Fine-tuned Large Language Models for domain-specific AI applications.
- Designed prompt engineering workflows to improve LLM accuracy and response .
- Built machine learning models for classification, regression, and predictive .
Key Achievements / KPIs
- Built a production-ready LLM chatbot for automated customer support.
- Integrated RAG with FAISS/ChromaDB for context-aware knowledge retrieval.
- Implemented OpenAI APIs, prompt engineering, and conversation memory.
- Reduced manual support workload by automating FAQ and customer queries.
Areas of Expertise
AI & Machine Learning Engineers
Design, train, and ship production ML models — from data pipelines to model inference at scale. Covers supervised learning, neural networks, LLM integration, and model optimisation.
Data Science & Analytics
Extract business insights from raw data using statistical modelling, predictive analytics, A/B testing, and interactive dashboards.
NLP & Prompt Engineering
Build natural language processing systems, fine-tune large language models, and craft reliable production prompts for AI-powered products.
Automation & AI Workflows
Build intelligent automation pipelines, integrate AI APIs into existing tools, and replace manual workflows with agentic AI systems.
