Muhammad Muzammil Tariq

Led end-to-end delivery of production AI solutions across NLP, Generative AI, Computer Vision, and Agentic systems, reducing manual operational effort by 40-70%. Designed and deployed RAG-based enterprise knowledge systems enabling instant access to structured and unstructured data and cutting information retrieval time by 60%+. Built and maintained scalable backend microservices architecture using FastAPI, Docker, and PostgreSQL, supporting 10k+ monthly API requests with high availability. Optimised LLM inference pipelines using vLLM, batching, and quantisation, reducing AI infrastructure costs by approximately 35%. Integrated AI services into business workflows using n8n, Flowise, and Prefect, enabling automation across support, analytics, sales, and internal tooling. Implemented CI/CD pipelines for AI and backend services, enabling automated testing, builds, and deployments. Delivered AI systems supporting multiple internal teams and client-facing products in production environments

Delivered AI-driven automation and data engineering solutions for UK-based clients across recruitment, marketing, and e-commerce. Designed and operated large-scale scraping and enrichment pipelines processing 100k+ profiles per month; built ML models for text classification, entity extraction, ranking, and analytics-driven decision systems.

Designed and deployed agentic AI assistants for sales, marketing, customer support, and internal operations. Built AI-driven outreach, analytics, and recommendation systems across multiple business domains.