I am a Machine Learning and Software Engineer specializing in building scalable, production-ready AI systems. My work sits at the intersection of machine learning, DevOps, and cloud infrastructure, where I design automated ML pipelines, containerized services, and CI/CD workflows to bring models from experimentation to reliable production. I have hands-on experience with Python, PyTorch, TensorFlow, Docker, Kubernetes, and AWS, and have built ML-powered SaaS platforms involving GPU acceleration, asynchronous job processing, and real-time monitoring. I enjoy collaborating closely with data scientists and engineers to embed MLOps best practices that improve reproducibility, observability, and system reliability.

Jiano Freo Magtangob

I am a Machine Learning and Software Engineer specializing in building scalable, production-ready AI systems. My work sits at the intersection of machine learning, DevOps, and cloud infrastructure, where I design automated ML pipelines, containerized services, and CI/CD workflows to bring models from experimentation to reliable production. I have hands-on experience with Python, PyTorch, TensorFlow, Docker, Kubernetes, and AWS, and have built ML-powered SaaS platforms involving GPU acceleration, asynchronous job processing, and real-time monitoring. I enjoy collaborating closely with data scientists and engineers to embed MLOps best practices that improve reproducibility, observability, and system reliability.

Available to hire

I am a Machine Learning and Software Engineer specializing in building scalable, production-ready AI systems. My work sits at the intersection of machine learning, DevOps, and cloud infrastructure, where I design automated ML pipelines, containerized services, and CI/CD workflows to bring models from experimentation to reliable production.

I have hands-on experience with Python, PyTorch, TensorFlow, Docker, Kubernetes, and AWS, and have built ML-powered SaaS platforms involving GPU acceleration, asynchronous job processing, and real-time monitoring. I enjoy collaborating closely with data scientists and engineers to embed MLOps best practices that improve reproducibility, observability, and system reliability.

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Experience Level

Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Intermediate
Intermediate
Intermediate
Intermediate
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Language

English
Fluent

Work Experience

. at ..
June 1, 2025 - Present
Software Engineer Intern
September 1, 2025 - November 1, 2025
Front-end development using Tailwind CSS and Material UI; delivered stylistic, responsive interfaces aligned with cosmetics and spa brand aesthetics.

Education

Bachelor of Science at Technological University of the Philippines
September 8, 2023 - April 16, 2027
Relevant Coursework - DSA, OOP, Statistics, Computer Science, Business

Qualifications

Risk Analysis for Project Management
January 11, 2030 - January 4, 2026
Teaching and Learning in Modern ICT
January 1, 2025 - January 1, 2030

Industry Experience

Software & Internet, Computers & Electronics
    paper Meta Ecommerce Aggregator Application – Full-Stack AI deeplearning Monorepo

    Built deeplearning pnpm-powered monorepo aggregating deals from Amazon, eBay, and Shopify.
    Developed with NestJS, Next.js, PostgreSQL, Redis, and Meilisearch for scalable search.
    Implemented ML models for price trend prediction and optimal buying windows.
    Designed weighted scoring algorithm to rank offers by price, shipping, and seller rating.
    Applied collaborative filtering for personalized recommendations across marketplaces.
    Achieved sub-100ms search over millions of SKUs with TypeScript full-stack orchestration.

    paper InfiniteFlow AI – Full-Stack ML SaaS Platform

    Built ML SaaS for video frame interpolation using RIFE with GPU acceleration.
    Designed scalable architecture with async jobs, task queues, and real-time tracking.
    Developed web interface for video upload, status monitoring, and output download.
    Added AI-assisted prompt controls for guided video enhancement.
    Delivered end-to-end system design across frontend, backend, GPU, and DevOps.