About
Hi, I’m Bagus, an AI/ML Engineer and Software Developer focused on building machine learning systems and turning them into practical software products across web, mobile, and iOS. I’m particularly interested in computer vision, on-device ML, and building reliable AI applications with techniques such as RAG, prompt engineering, and guardrails.
Currently, I’m at the Apple Developer Academy @ Infinite Learning Batam, where I work with multidisciplinary teams to solve real-world problems through design thinking, rapid prototyping, and native iOS development. My work includes building on-device ML features with Apple frameworks such as CoreML and Vision, while continuing to explore modern AI engineering through projects involving RAG and LLM-based applications.
Outside of tech, I like exploring things that are a little different from my usual screen time. I sketch and draw, sing and cover music, go to the gym, and spend time traveling into nature.
Experience
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MAR 2026 - Present I designed and shipped native Apple ecosystem applications at Infinite Learning in Batam, focusing on watchOS fitness companions and on-device CoreML intelligence.
- Swift 6
- SwiftUI
- CoreML
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SEP - DEC 2025 During my 4-month internship at PT SPIL in Tanjung Priok, I developed internal predictive systems and web dashboards to support maritime crew health alerts and container vessel operations.
- Python
- React.js
- Flask
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JUN - SEP 2025 During my internship at Telkom DDB, I conducted field research with greenhouse tomato farmers in Lembang and designed the Decision Support System architecture for the greenhouse project.
- Python
- DSS Architecture
- System Design
Projects
Arterious: Family Health Monitoring iOS App
A family health awareness iOS app that bridges distance by tracking parental wellness indicators through Apple HealthKit, CloudKit private sharing, and Google Gemini LLM insights.
Footsal: Tracking Sports Balls in Real Time on a Tripod-Mounted iPhone
How I built an on-device ball tracking and pose detection pipeline using YOLO11m, CoreML, and Apple Vision for amateur futsal analytics.
RONA: Quantizing YOLO26s to 9.3 MB for On-Device Acne Tracking
How my 10-person team built an offline iOS skin recovery assistant with three-angle scans, CoreML quantization, and Apple Neural Engine acceleration.
Writing
Building My Own Neural Twin: What Making a Production RAG Chatbot Taught Me About AI Engineering
I wanted my portfolio to answer questions about me. I didn't expect the hard part to be teaching an AI when it shouldn't answer.
- Personal Blog
From 'Just a Bot' to AI Agents: How My World Shifted in 4 Years
A personal reflection on how AI went from a chatbot that couldn't answer my first-year college quiz in 2022 to autonomous agents helping me build and deploy software in 2026.
- Personal Blog
Multimodal Information Credibility Classification Using CNN-BiGRU with Particle Swarm Optimization
For my undergraduate thesis, I developed a multimodal deep learning pipeline combining text, images, and user metadata with Particle Swarm Optimization, which was published at IEEE ICICyTA.
- IEEE Paper
Awards
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2024 Awarded 1st Place out of 100+ project teams nationwide in Telkom Indonesia's digital incubation program, evaluated by the CDIO of TelkomGroup.
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2024 Awarded university venture funding from Kemendikbudristek RI for Eleganza, a rental platform for traditional Indonesian fashion.
Playground & Lab
Location
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Tech stack
Tech stacks I'm familiar with
Focused on Core ML, SwiftUI, Python, and Foundation Models.