Muhammad Awan

Architected AI-driven smart city systems with predictive analytics and infrastructure optimization models. Designed scalable ETL and ML pipelines for real-time decision-making and built analytics dashboards for stakeholders.

Led full lifecycle development of enterprise-grade LLM applications, including data pipelines, SFT and RLHF fine-tuning, and deployment. Built scalable RAG pipelines and evaluation frameworks, improving model accuracy by 35%+ across multiple enterprise use cases.

Delivered end-to-end AI solutions for global clients across healthcare, fintech, e-commerce, education, and enterprise systems. Built production-integrated chatbots, NLP pipelines, automation tools, and recommendation engines, managing scoping through monitoring and optimization.

Developed computer vision pipelines for image recognition, classification, and content recommendation. Built recommendation systems that improved content personalization by 40% and implemented automated labeling/augmentation to speed up training.

Developed a full-stack AI platform for audio and sensor analytics using machine learning and computer vision. Built real-time streaming ingestion and processing pipelines and integrated LLMs for predictive insights, anomaly detection, and audio content analysis.

Designed and delivered end-to-end AI automation systems, reducing client workflow bottlenecks by 50%. Built NLP pipelines for intelligent document processing, semantic search, and summarization, and integrated AI into SaaS for real-time insights.

Built an AI-powered SaaS platform for enterprise clients integrating NLP, LLMs, and automation features. Designed scalable backend APIs, data pipelines, and AWS/GCP infrastructure, and optimized performance and CI/CD for production deployments.

Built AI-driven healthcare analytics and predictive models to improve patient outcomes. Implemented diagnostic recommendation engines and improved clinical decision support accuracy by 30%, with end-to-end ML pipelines from ingestion to deployment and monitoring.

Led AI-first e-learning and e-commerce platform development with full ownership of technical strategy. Scaled the platform to 10,000+ daily active users, improving load speed by 50% and engagement by 40% through personalization, recommendation, and predictive models.

Built an AI auditing suite to analyze model bias, fairness, and compliance across enterprise AI systems. Developed explainability and monitoring tools, and performed end-to-end LLM/ML evaluation with actionable recommendations.

Built backend systems integrating ML models for enterprise clients, including scalable APIs and data pipelines. Optimized system performance and improved AI model efficiency for production usage.

Delivered real-time data pipelines and monitoring tools across multiple client industries. Built end-to-end AI solutions for domains including hotel management, accounting, and education, improving system performance and model scalability.

Completed a Bachelor’s in Computer Science at Punjab University College of Information Technology from 2009 to 2013.