DOSSIER
Mugni Hidayah
AI Engineer focused on building end-to-end LLM and machine learning systems and turning them into practical, production-ready applications.
EMAILmugnihidayahwork@gmail.com
LOCATIONIndonesia
EDUCATIONBachelor of Data Science · Telkom University
CREDENTIALS7+ verifiable certifications
2
FEATURED PROJECTS
1
SELECTED EXPERIENCE
LLM · RAG · ML
CORE DOMAINS
KEY STRENGTHS
AI Engineering
- Build LLM apps, RAG systems, APIs, orchestration flows, and product-minded AI backends.
- Comfortable owning the path from prototype logic into deployable application behavior.
- Think in terms of reliability, architecture, evaluation, and user-facing delivery.
ML & Data Foundations
- Data Science degree: statistics, experimentation, machine learning, and model evaluation.
- Comfortable turning raw data into features, signals, and metrics that ground AI systems.
- Evaluate before shipping — a data-first mindset applied to every model and pipeline.
SELECTED ACHIEVEMENTS
01
Built a production-minded multimodal RAG backend
Designed Synapse with hybrid retrieval, citations, auth, rate limiting, analytics, and session exports to move beyond a notebook-style demo.
02
Shipped a full-stack AI interview simulator
Built Interview AI across frontend, backend, multi-agent orchestration, streaming UX, voice mode, and model fallback behavior.
03
Delivered a real-time CV analytics system
Reached 30–60 FPS on an RTX 3050 while combining detection, emotion classification, smoothing, and dashboard visualization.
04
Improved large-scale data workflows during internship
Processed 1M+ transaction records efficiently and handled 10,000+ imbalanced reviews through automated text classification.
FOCUS & TOOLING
DOMAIN FOCUS
AI EngineeringData ScienceLLM ApplicationsRAG SystemsAI AgentsComputer Vision
TOOLS I REACH FOR
FastAPIGitHuggingFaceLangChainPandasPythonPyTorchDocker
WHAT I'M LOOKING FOR
- AI Engineer opportunities where I can build practical LLM, RAG, and intelligent application workflows.
- Products where evaluation, reliability, and real user impact matter more than flashy demos.
- Teams that value end-to-end ownership — from data thinking and model iteration to product-ready delivery.
ELSEWHERE