Open to opportunities

Camilo CovHer

@mxtxtrxn

I’m a Machine Learning Engineer building industrial computer-vision systems that detect, segment, and analyze defects in production.

Mexico

Message

What I'm looking for

I’m looking for remote or contract opportunities where I can deploy computer-vision ML to real factories, improve workflow efficiency with end-to-end pipelines, and collaborate with engineers to turn operational problems into measurable results.

I’m a Machine Learning Engineer specialized in Computer Vision solutions deployed in real industrial environments. I design, train, and optimize deep learning models for detection, segmentation, and defect analysis—translating operational problems into scalable ML-driven improvements for industrial workflows.

My work blends machine learning with backend development and embedded systems integration, enabling end-to-end intelligent systems from data acquisition to production deployment. I’ve built and deployed systems using YOLO and Segment Anything, and integrated embedded platforms to automate verification and reduce operational inefficiencies.

Experience

Work history, roles, and key accomplishments

Current

Machine Learning Researcher

Current

University of Guanajuato

Jan 2024 - Present (2 years 6 months)

Designed and implemented neural network models for materials characterization, training and optimizing YOLO and Segment Anything for segmentation and feature extraction. Built image preprocessing pipelines and integrated embedded systems to improve industrial sampling processes, documenting results in research collaborations.

Python PyTorch TensorFlow YOLO Segmentation OpenCV data preprocessing Embedded Systems Git

Machine Learning & Software Engineer

CDSOFT IT

Jan 2023 - Jan 2024 (1 year)

Developed and deployed a Raspberry Pi-based embedded Poka-Yoke system for real-time industrial component verification and parts counting in Nissan assembly workflows. Built C# backend systems and full-stack web apps (Node.js, HTML/CSS, MySQL) for inventory and order management, using computer vision to reduce production human error.