AI Engineer & Data Scientist — Indonesia

Muhammad
Nuril Huda

Building practical AI systems from data, models, and real-world workflows.

I turn messy data and manual processes into AI-powered products — combining engineering judgment, model evaluation, data reasoning, and product execution.

  • M.Cs. Computer Science, UGM
  • Founder, Aureum
  • LLM Evaluation — Alignerr & Outlier
  • Python · FastAPI · PySpark · Docker · AWS · GCP
Portrait of Muhammad Nuril Huda wearing a maroon batik shirt against a dark background

About

Ambiguous problems in. Working systems out.

I work at the intersection of AI engineering, data science, and product execution. My strength is turning unclear operational problems into structured systems: define the workflow, reason about the data, evaluate model behavior, and ship something people can actually use.

My background spans LLM evaluation, AI product development, forecasting pipelines, backend-driven RAG applications, and medical computer vision research. I care about practical usefulness: AI that gives clear explanations, handles real constraints, and supports better decisions.

What I build

Four kinds of systems.

LLM & GenAI Systems

Practical AI workflows using RAG, prompt orchestration, structured outputs, and model evaluation patterns that prioritize correctness and usefulness.

AI Product Engineering

Backend-driven AI applications with Python, FastAPI, Docker, relational workflows, caching, and cloud deployment.

Data Science & Forecasting

Data pipelines, analytics workflows, and forecasting systems using Python, SQL, PySpark, SARIMA/LSTM, and stakeholder-ready reporting.

Computer Vision & Medical AI

Research and project experience in thermal imaging, deep learning, image enhancement, face/deepfake detection, and video intelligence pipelines.

Featured work

Selected systems & projects.

AI products, LLM evaluation, data pipelines, and applied computer vision.

Founder · AI Product

Aureum — AI Financial Copilot

Founded and built an AI-powered financial copilot that helps users manage personal finances and make better investment decisions through natural conversation — AI orchestration, financial analytics, market intelligence pipelines, and cloud infrastructure, with transparent, non-custodial recommendations.

  • AI orchestration
  • Financial analytics
  • Market intelligence
  • Cloud infrastructure

GenAI · Computer Vision · Media

Ayclip — AI Video Clipping Pipeline

AI-powered video clipping architecture that turns long-form video into short-form clips: YOLOv11 + MediaPipe + ByteTrack for face tracking and 9:16 auto-reframing, Claude-based semantic highlight detection, Whisper speech-to-text with word-level subtitle synchronization, and asynchronous processing on Docker and AWS ECS/S3.

  • Python
  • FastAPI
  • Celery
  • YOLOv11
  • MediaPipe
  • ByteTrack
  • Whisper
  • FFmpeg
  • Docker
  • AWS ECS/S3

LLM Evaluation

Alignerr — LLM Evaluation & Code Review

Evaluating AI-generated STEM, coding, ML, and data science reasoning: reviewing code for logic errors and edge cases, producing structured feedback for LLM training workflows, and auditing annotation quality against rubrics.

  • Python
  • Rubric evaluation
  • RLHF/SFT
  • QA workflows

RAG · Backend AI

Hospital Chatbot Appointment System

Backend-driven medical chatbot combining a LangChain RAG pipeline, document retrieval, multi-intent handling, and automated doctor assignment — turning a manual appointment workflow into an AI-assisted service.

  • Python
  • FastAPI
  • Docker
  • LangChain
  • RAG
  • Caching

AI Assistant · DS Tooling

DeciSense — AI Assistant for Data Science Workflows

Python-based assistant automating data science workflows: dataset intake, validation, profiling, task inference, planning, modeling, evaluation, and reporting — simple inspectable logic first, LLM assistance second.

  • Python
  • Data validation
  • Profiling
  • ML planning
  • LLM explanations

Data Science · Forecasting

Transportation Demand Forecasting

Forecasting pipelines integrating taxi, flight, and weather datasets on PySpark and GCP with SARIMA and LSTM models — improving prediction accuracy by 15% and cutting pipeline runtime by 90%.

  • Python
  • PySpark
  • GCP
  • SARIMA
  • LSTM

Case-study details for each system are available on request.

Capability matrix

Technical capability, grouped by function.

AI Engineering & LLM Systems

  • Agentic AI & multi-agent systems
  • MCP (Model Context Protocol)
  • RAG · hybrid retrieval · reranking
  • Vector databases
  • LangChain / LangGraph
  • Context & prompt engineering
  • Structured outputs & tool calling
  • LLM evaluation & LLM-as-judge
  • RLHF/SFT evaluation
  • Guardrails & AI safety
  • Prompt caching & cost optimization
  • Voice & multimodal AI

Backend & AI Product Engineering

  • Python
  • FastAPI
  • REST APIs
  • SQL
  • Caching
  • Docker
  • Git
  • Celery
  • Workflow automation

Data Engineering & Analytics

  • PySpark
  • ETL pipelines
  • Batch processing
  • Schema design
  • BigQuery
  • Looker Studio
  • Dashboard design
  • Reporting automation

Data Science & Machine Learning

  • Time-series forecasting
  • SARIMA
  • LSTM
  • Statistical analysis
  • Clustering
  • Classification
  • Regression
  • Feature engineering
  • Model evaluation

Computer Vision & Media AI

  • OpenCV
  • CNN classification
  • Medical image analysis
  • Thermal imaging
  • Deepfake detection
  • YOLOv11
  • MediaPipe
  • ByteTrack
  • Whisper
  • FFmpeg

Cloud & Deployment

  • AWS ECS
  • AWS S3
  • CloudFront
  • GCP
  • BigQuery
  • Compute Engine
  • Vertex AI
  • Streamlit
  • Static hosting

AI-Accelerated Engineering

I build with AI, not just build AI — agent-assisted development is how I ship faster than team size suggests.

  • AI coding agents (Claude Code)
  • Spec-driven development
  • AI code review & auditing
  • Eval-driven development
  • LLM training data quality
  • Human-in-the-loop workflows
  • Rapid AI prototyping

Product, Research & Collaboration

  • Business problem framing
  • Technical documentation
  • Stakeholder reporting
  • Async collaboration
  • Fast iteration
  • Startup leadership
  • Research writing

Experience

Seven roles. One direction.

  1. Jan 2026 — Present

    Founder · Aureum

    Building an AI financial copilot end to end: AI orchestration, financial analytics, market intelligence pipelines, and cloud infrastructure.

  2. Mar 2026 — Present

    AI Engineer · Ayclip

    Designing AI video clipping architecture: CV pipelines, semantic highlight detection, ASR/subtitles, and asynchronous media processing on AWS.

  3. Oct 2024 — Present

    AI Evaluation Consultant · Alignerr

    Evaluating AI-generated STEM/coding/ML solutions, reviewing code quality, and auditing annotation outputs for rubric adherence and reasoning quality.

  4. May 2024 — Oct 2025

    AI Trainer & LLM Evaluator · Outlier

    Reviewed and annotated AI responses for RLHF/SFT across general, technical, and CS domains; assessed instruction-following, truthfulness, and reasoning.

  5. Jan 2024 — Jul 2024

    Data Scientist Intern · Data Glacier

    Built PySpark/GCP pipelines integrating taxi, flight, and weather data; SARIMA & LSTM forecasting improved accuracy 15% and cut runtime 90%.

  6. 2023

    Data Analyst Fellow · GoTo Impact Foundation

    Designed dashboards and automated reporting for student performance tracking; translated findings for non-technical stakeholders.

  7. Aug 2021 — Feb 2022

    AI Engineer Apprentice · Orbit Future Academy

    Led a team of four building a deepfake detection system with CNN architectures (MTCNN, InceptionResNetV1), from preprocessing to evaluation.

Research & education

Medical computer vision research.

Master's thesis · Universitas Gadjah Mada

Early detection of diabetic foot ulcers using thermogram and temperature data integration

97.06% reported classification accuracy

Combined plantar thermogram imaging with temperature data to detect diabetic foot ulceration risk early — image enhancement, feature integration, and rigorous model evaluation.

Published in SINTECHCOM Journal, Feb 2025 · DOI 10.59190/stc.v5i2.273

Education

M.Cs. Computer Science

Universitas Gadjah Mada · GPA 3.79/4.00

Education

S.Kom. Informatics

Universitas Muhammadiyah Malang · GPA 3.86/4.00

Book

Java Itu Mudah

DIVA Press, 2020 · ISBN 9786023918980

Contact

Let's build something practical.

Interested in AI engineering, GenAI, LLM systems, data science, or applied AI product work? Reach me directly by email or LinkedIn — I'm open to roles and collaborations.

nurilhuda3333@gmail.com