AI/ML Engineering
Designing and deploying production-grade AI systems—from RAG pipelines and multi-agent architectures to end-to-end MLOps on multi-cloud infrastructure.
Muhammad R. B. Noerrahman
Senior Machine Learning Engineer
Machine Learning · Artificial Intelligence · Finance · Theoretical Physics
Currently heading the model.fit() efforts with my team
at Solusi247
About
A Multidisciplinary Builder
I started in theoretical physics—drawn to fundamental questions about how things work. That curiosity led me to artificial intelligence, then to finance, and eventually to leading engineering teams building production AI systems. The thread through all of it is simple: I love getting to know how everything works, building things and solving hard problems with brilliant people.
Today I lead a team of data scientists and ML engineers, designing and deploying AI/ML solutions that turn ambitious ideas into real, recurring revenue. My approach blends technical depth with business pragmatism—I care as much about why we’re building something as how we can build it effectively.
8+
Data Scientists and ML Engineers Led
25+
Production-scale AI/ML
Pipelines Delivered
Pipelines Delivered
10+ Years
Across 3 Disciplines
What I Do
Areas of Expertise
Data Science Mastery
There's no AI/ML model without data science, thorough understanding of the data science work flow from exploratory data analysis all the way to data storytelling.
Multi-domain Understanding
Academic background in physics, artificial intelligence and finance. Paired with project experience in logistics, telco and government sectors to name a few.
Technical Leadership
Leading teams of data scientists and ML engineers with a focus on code quality, agile delivery, and aligning technical roadmaps with business strategy.
Strategic Planning
Translating technical capabilities into business value. Bridging the gap between engineering teams and C-level stakeholders to drive data-informed decisions.
Applied Research
Exploring the frontier of context engineering, agentic AI, and sensor fusion—turning research into practical, deployed solutions that solve real problems.
Work Experience
Where I’ve Worked
PT. Dua Empat Tujuh
Oct 2025 – Present
Senior Machine Learning Engineer
Jakarta, Indonesia
- Lead a team of 6 data scientists and 2 ML engineers across AIOps (AI for Data Operations), taking the platform from its second production phase to a third phase
- Own development, maintenance, and monitoring of production AI/ML systems: 25+ traditional ML pipelines for forecasting, anomaly detection, and classification, plus 8 agent-based generative AI pipelines
- Lead LLM integration across AIOps and internal products, with applied research in RAG, context engineering, prompt management, and agentic AI
- Built a modular LangGraph agentic AI framework reused across an OSINT situation room and weekly newsletter generator, cutting newsletter turnaround from days to hours
- Set engineering practices for pipeline documentation, code review, sprint planning, and production AI-assisted coding; wrote a company-wide spec-driven development playbook
- Serve as one of four business development officers, evaluating opportunities, advancing partnership discussions, and contributing to commercial strategy
PT. Dua Empat Tujuh
Oct 2023 – Sep 2025
Data Scientist (ML Engineering)
Jakarta, Indonesia
- Served as project-level Data Science Team Lead for AIOps from its proof-of-concept first phase to its production second phase, leading 2 data scientists and 2 ML engineers
- Owned delivery end-to-end: high-level solution architecture, requirements gathering, sprint planning, AI/ML system design, coding, code reviews, debugging, and dashboard development
- Ran the full data-science lifecycle ahead of engineering — exploratory data analysis, statistical modelling, experimentation, and model evaluation — grounding every pipeline in validated evidence
- Guided an internal research team building a stock-market monitoring dashboard and alpha generation for the Indonesian market, now fully operational under business development
- Developed real-time navigation and drift correction for an autonomous system using sensor fusion (extended Kalman filter), zero-velocity update, and quaternion-based IMU data, achieving <2m position error over 1km with embedded engineering teams
- Advised internal C-level stakeholders, aligning technical roadmaps with strategic business priorities; formed a cross-functional business development team for financial analytics-driven growth and commercial strategy
Freelance
Jan 2023 – Sep 2023
Data Scientist
Self-Employed
- Delivered end-to-end ML consulting: data collection, model development, and production deployment for multiple clients
- Communicated technical results to non-technical domain experts, driving data-informed decisions
- Developed a classifier model for an energy-sector client, surfacing preliminary insights on samples before they are sent to an external organisation for full analysis
Nomura Research Institute Indonesia
Jan 2022 – Dec 2022
Machine Learning Engineer
Jakarta, Indonesia
- Developed ML models and data product prototypes from multi-cloud, TB-scale telematics and operational data
- Performed ETL on economics time-series, geospatial, and statistical data from sources ranging from the Indonesian Government to the World Bank
- Collaborated with cross-functional teams to optimise ML models in Python and integrated them with production systems to automate decision-making
Projects
Selected Work
AI for Data Operations
2023 – Present
Led cross-functional team to design, deploy, and maintain scalable AI/ML solutions for data operations, transforming initial PoC into recurring revenue project (now in third phase). Implemented Kubeflow pipelines, monitoring with Grafana, and established ML model lifecycle management. Delivered significant improvements in incident detection and response time while reducing monitoring overhead.
Agentic AI Framework for Media Analytics
2025
Built modular multi-agent framework (LangGraph) deployed on OSINT situation room and weekly newsletter generator for media analytics platform. Demonstrated cross-product reusability of agent architectures. Reduced newsletter generation time from days to hours.
Inertial Navigation for Autonomous System
2025
Developed inertial navigation algorithms using sensor fusion (Extended Kalman Filter) and Zero Velocity Update for real-time drift correction in autonomous systems. Achieved <2m position error over 1km through collaboration with embedded engineering teams.
Telematics Data Analytics
2022
Developed ML-based predictive maintenance model and vehicle breakdown root cause analysis utilising vehicle telematics and geospatial data on AWS. Identified potential locations of low-quality, unregulated fueling spots across Indonesia.
Data Science Techniques in Stock Portfolio Management
2022
Applied linear regression, clustering (asset selection), and Monte Carlo methods for portfolio construction. Extracted Alpha, Beta, Sharpe, and Sortino Ratios from stock price time-series data. github.com/mrizzben/idx-stocks-analysis
portagent
2026
Phone-sized Rust TUI that watches coding agents (pi, Claude Code, Codex and others) across tmux, showing live activity and keeping a session ledger. github.com/mrizzben/portagent
revis.io
2026
Weekend-to-product build: a version-control and collaboration tool for architects and design professionals. github.com/mrizzben/revis.io
Education
Education
MBA in Finance
Cum Laude
Universitas Gadjah Mada
Aug 2019 – Jan 2022
GPA: 3.97/4.00. Top graduate of the
International Programme Batch 75; second-highest GPA of all
graduating classes. Relevant coursework: Statistics for Business
Decision, Financial Management, Technology and Operations
Management. Thesis:
Implementation of Data Science Techniques in Stock
Portfolio Management.
International Exchange Semester
Toulouse Business School, Toulouse, France
Jan 2021 – Jun 2021
Relevant coursework: Financing and Financial Securities,
Financial and Debt Markets, International Financial Management.
PGCert Artificial Intelligence
University of Edinburgh
Sep 2016 – Nov 2017
Relevant coursework: Machine Learning and Pattern Recognition,
Probabilistic Modelling and Reasoning. Neural Information
Processing, Neural Computation.
Machine Learning Practical Coursework.
BSc (Hons) Theoretical Physics
First Class Honours
Swansea University, Swansea, UK
Sep 2012 – Jul 2016
Degree Average: 73.6%. Graduated top of the
programme. Relevant coursework: Differential Equations,
Quantitative Methods, Mathematical Methods, Physics Simulation.
Undergraduate project:
One-way Quantum Computation — An Introduction to
Measurement-based Quantum Computation.
Stanford Summer Programme
Stanford University
Jun 2014 – Aug 2014
Relevant coursework: Programming Methodology.
Toolkit
Technologies & Tools
Technologies and tools I work with daily
Languages & Tools
ML/AI Frameworks
LLM & Generative AI
MLOps & Deployment
Visualisation
Database
Cloud
Geospatial
Languages
Soft Skills
Recognition
Recognition & Awards
Excellent Graduate of International Class
2022
Top graduate of the International MBA class, April 2022 graduation batch.
Best Physics Final Year Project
2016
Swansea University Physics Department — One of two recipients selected from 100+ graduating physics students.