Emaan Siddiqui

I am a results-driven AI Engineer with a strong background in building and deploying LLM-powered systems for various applications, including classification, speech processing, and automation. My expertise lies in fine-tuning, RAG, prompt engineering, and agentic workflows across multimodal and audio-to-audio AI. I have hands-on experience with technologies such as PyTorch, Hugging Face, and Azure OpenAI, enabling me to deliver high-quality solutions that meet complex requirements.

Throughout my career, I have achieved significant milestones, such as automating annotation for Medicare intent labels with a remarkable 95% accuracy using GPT-4o-mini and developing a real-time audio-to-audio accent converter with minimal latency. My work at Confinality and Imperium Dynamics has honed my skills in creating efficient AI solutions that enhance productivity and streamline processes. I am passionate about leveraging AI to solve real-world problems and continuously seek opportunities to innovate and improve.