I build production AI systems, RAG pipelines, and LLM apps trained by IBM, Stanford & DeepLearning.AI.
I'm Hamayl, an AI Engineer focused on building intelligent systems that combine computer vision, large language models, and modern AI architectures. My work centers on transforming AI research into reliable, production-ready solutions.
A structured, technical process for turning a research idea into a deployed, monitored AI system.
Scope the problem, the data available, and the constraints, latency, hardware, accuracy bar, before writing any model code.
Architect the pipeline, preprocessing, model choice, retrieval layer if needed, as a system, not a single notebook cell.
Train, fine-tune, and optimize for inference, augmentation, hyperparameter sweeps, and benchmarking against the constraint.
Ship to Streamlit, Gradio, or an API, then monitor, gather feedback, and iterate on the live system.
From real-time object detection to retrieval-augmented generation, each one built end-to-end, not a tutorial clone.
LIVE
LIVE
LIVE
Six specializations across machine learning, deep learning, and generative AI — completed end-to-end, not skimmed.
Complete 13-course specialization covering the full AI engineering pipeline.
Supervised, unsupervised learning, and advanced ML systems.
Neural networks, CNNs, RNNs, sequence models, and hyperparameter tuning.
Practical deep learning across the three leading frameworks.
LLMs, transformers, and generative architectures for NLP applications.
End-to-end data analysis pipelines, visualization, and statistical insight.
A real, working RAG-powered assistant trained on my own work and experience. Ask it anything about my projects, skills, or background, it's live right now.
Open to AI/ML engineering roles, freelance computer-vision and LLM work, or just a conversation about an idea you want to turn into a deployed system.