Afiq CM here. あざっす。
By day, I work with data: refining feature stores, building models, crafting pipeline workflows, and scaling data insight solutions.
By night, I write about the parts of engineering they don't tell you to your face: being a first-generation professional, managing upwards, having agency, navigating local corporate structures, and the invisible dynamics of a career.
About
2012: Performing in Kangar with the varsity brass band, not knowing how my future would unveil itself.
2018: Registered for MPhil and welcomed my daughter, starting the early transition away from electronics engineering.
2021: Saying goodbye to one of the best teams I've worked with. A reminder that in any job, stint, or gig, it is the people you build with that matter most.
Hello there! I'm Afiq. Afiq CM. I've been an early member of founding machine learning & data teams across various companies. Currently I'm in fintech working on tabular ML, but my experience spans propensity models at CIMB, recommendation systems at Popsical, and ML and computer vision systems at Ørsted, BAT, and Moovita, as well as freelancing with a Japanese startup. I've always been keen to bridge the gap between business & data science, as well as making a solution workable & scalable.
I've always loved AI/ML research and maths to an extent, as well as the impact of AI on our daily lives. More recently, I've been exploring AI agents and NLP. Outside of tech, I've spent time ghostwriting travel articles for online platforms. In another life, I probably would have ended up as a linguist, a dancer (personally I think it's a stretch myself, but hey - one can dream!), or a music creator.
Current Interests & Focus
60% Technical
- Tabular ML & deployment
- Machine learning frameworks (Scikit-Learn, PyTorch, TensorFlow)
- NLP & autonomous AI agents
40% Human
- Bridging the business-to-data gap
- Delivering results within resource constraints
- Upward management & career agency
Thoughts
A digital garden mapping the intersection of data, engineering, and career realities.
Work
Selected systems, analytics pipelines, and engineering projects.
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Propensity Modeling 01
Consumer Loan Propensity Model & On-Prem Feature Store
Spearheaded the development of ensemble propensity models and optimized local feature stores on-premise, generating a $200,000 revenue increase from improved consumer personal loan leads. Read the project post-mortem →
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Autonomous Vehicles 02
LiDAR-Based AV Object Detection Pipeline
Designed and deployed LiDAR point-cloud processing and object detection pipelines using SqueezeSeg and PointPillars, resolving edge-case detection issues for real-world autonomous driving safety. Read about working with point clouds →
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Predictive Modeling 03
Automated Pricing & Volume Forecasting Models
Optimized automated volume forecasting and pricing pipelines using linear regression and decision trees, achieving over $1,000,000 in operational cost savings. Read the pricing model lessons →
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Generative AI 04
GANs for Building Occupancy Modeling
Developed a Generative Adversarial Network (GAN) architecture during my research at UTM to model and simulate occupancy patterns in smart building systems. Read the research notes →
Currently refreshing my deep-dive case studies. In the meantime, check out my latest notes on the blog.