rashaad nmohammed

I’m a Machine Learning Engineer building applied AI systems, currently pursuing a B.Tech in Artificial Intelligence and Machine Learning. In a startup/freelance role, I designed and optimized ML models for classifying web vulnerabilities, improving automated pentesting triage efficiency by 30%.

I engineer end-to-end pipelines—from data collection and feature extraction to training, inference, and reporting. I’ve also fine-tuned transformer models on security datasets, achieving an 18% increase in classification accuracy and reducing false positives by 30%, while generating structured penetration testing reports with ML-based risk scoring and remediation recommendations.

I enjoy building efficient, production-ready solutions like distributed multi-agent systems for parallel endpoint scanning (reducing analysis time by 65%). Beyond security workflows, I’ve developed an offline AI voice assistant and RAG pipeline with persistent memory, improving response relevance by 25% and enabling edge deployment through quantization and pruning.