Mubbashir Hassan

As an AI Engineer and Applied Machine Learning Specialist, Mubbashir drives the design and development of intelligent, production-grade systems that bridge the gap between research and real-world impact. His work spans LLM-based applications, voice AI agents, machine learning pipelines, and automation frameworks, empowering organizations to scale faster and make data-driven decisions with confidence.

Mubbashir’s expertise lies at the intersection of AI product development and system architecture. He has engineered scalable backends for agentic AI systems, voice-enabled assistants (via LiveKit, Deepgram, and ElevenLabs), resume analyzers, and marketing automation agents—integrating LLMs, NLP, and multi-agent orchestration with robust infrastructure layers built on FastAPI, Flask, and MongoDB.

With a foundation in Python, data science, and deep learning, Mubbashir translates complex algorithms into deployable, maintainable software systems. His architectural approach emphasizes low-latency communication, data security, CI/CD automation, and cloud-native scalability, ensuring that every AI product he builds is as reliable as it is intelligent.

Beyond engineering, Mubbashir is passionate about mentoring teams, enabling developers to understand not just how to build AI systems—but how to design them for real-world robustness and long-term sustainability.

He continues to explore advancements in transformer fine-tuning, LoRA/QLoRA optimization, and agentic automation, positioning himself and his teams at the forefront of the AI transformation era.