Salman Akram

AI and Backend Engineer with a Master’s degree in Artificial Intelligence and hands-on experience developing and deploying machine learning systems and scalable backend services. Skilled in Python, FastAPI, Docker, and modern ML frameworks including TensorFlow and PyTorch. Proven ability to build end-to-end AI solutions, from model development to production deployment, including healthcare AI systems and real-time data-driven applications. Strong problem-solving skills with a focus on delivering practical, business-driven solutions. Currently seeking opportunities in AI engineering, backend development, or MLOps.

• Developed a deep learning model using EfficientNet to classify multiple skin conditions with strong validation performance.
• Implemented Grad-CAM for model explainability.
• Built a FastAPI backend and React frontend for user interaction and report generation.
• Designed for real-world deployment with clinical safety considerations.

• Developed a stock prediction system using XGBoost with engineered features such as momentum, trend, and macroeconomic indicators.
• Integrated real-time market data and AI-based reasoning for decision making.
• Built a backend system to rank and select stocks for automated trading strategies.

• Built an intelligent chatbot for handling customer queries using Rasa.
• Implemented intent classification, entity extraction, and multi-turn conversation flows.
• Integrated fallback strategies and rule-based controls for reliability.