Professional Overview
AI/ML Engineer with 1.4 years of professional experience, including hands-on experience in building AI-powered applications, Generative AI solutions, and Retrieval-Augmented Generation (RAG) systems. Skilled in Python, FastAPI, LangChain, LLMs, vector databases, and Docker. Experienced in developing end-to-end AI solutions, integrating LLMs with enterprise data, building document-based question-answering systems, and deploying containerized applications. Familiar with MLOps concepts, Kubernetes, and machine learning model deployment. Passionate about building scalable, production-ready AI solutions and solving real-world business problems using AI.
Experience
Employment Type
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.
MLOps & AI Infrastructure
Architect scalable ML infrastructure — CI/CD for ML, model versioning, experiment tracking, monitoring, and cloud deployment on AWS, GCP, or Azure.
NLP & Prompt Engineering
Build natural language processing systems, fine-tune large language models, and craft reliable production prompts for AI-powered products.
