
Angel Carrillo-Bermejo is a machine learning engineer specializing in applying deep learning to solve real-world problems. He earned his BSc in Mechatronics Engineering from Universidad Modelo and an MSc in Computer Science from Universidad Autónoma de Yucatán (UADY). He began a PhD at Universidad Nacional Autónoma de México but chose to leave the program to focus on deploying AI systems in production.
Angel Carrillo-Bermejo has experience spanning applied research and production machine learning systems. During his PhD studies at the Universidad Nacional Autónoma de México (UNAM), he worked on a thesis developing a dissimilarity measure using chain codes in open curves, establishing mathematical foundations with potential applications in medical signals and imaging. He contributed to projects detecting anomalies in ocular blood vessels in premature and diabetic patients and explored machine learning approaches for identifying patterns in brain tumors and analyzing signals linked to conditions such as schizophrenia and Alzheimer’s disease.
Transitioning to industry, he has developed production-ready deep learning models for audio DeepFake detection and child grooming detection, designed flexible voice moderation pipelines with configurable analysis of age, speech, and emotion, and led large-scale infrastructure migrations to reduce operational costs. He also improved transcription throughput by optimizing language models to support scalable, high-performance systems. His work reflects a commitment to using AI to address critical challenges and deliver solutions with real-world impact.
“Nobody ever figures out what life is all about, and it doesn't matter. Explore the world. Nearly everything is really interesting if you go into it deeply enough.”― Richard P. Feynman.Deep neural networks are now the state-of-the-art machine learning models across a variety of areas, from image analysis to natural language processing, and are widely deployed in academia and industry. I am interested in applying these techniques to solve complex, real-world problems across sectors such as content moderation, security, healthcare, finance, and other domains where trustworthy and scalable AI systems can create value. My experience includes developing production systems for DeepFake audio detection, building child grooming detection algorithms, designing configurable voice moderation pipelines, optimizing transcription workflows to improve performance and efficiency, and creating deep learning models for medical imaging tasks like MRI data augmentation and tumor classification. I am passionate about contributing to innovative projects that leverage AI to drive impact in diverse industries.
You can find my all design work on GitHub, or if you wanto to look on my Profile on Linkedin. If you want to communicate with me, please send me an email or contact.
If you want to communicate with me, please send me an email.