Open to opportunities

Adli Ali

@adliali

Message

Machine Learning Engineer for anomaly detection and end-to-end ML systems solving rare-signal, high-noise problems.

Malaysia

Message

What I'm looking for

I’m open to senior remote industry roles where anomaly detection, rare-event modelling, and end-to-end ML system design are the substance—covering data-to-deployment pipelines with solid observability and monitoring.

I’m a Physics PhD Machine Learning Engineer with 10+ years building machine learning systems for rare-signal, high-noise problems—shaped through the CMS Collaboration at CERN searching for Beyond-Standard-Model physics in petabyte-scale experimental data. I focus on anomaly detection, one-class classification, and unsupervised representation learning.

I take strong ownership of end-to-end ML pipelines from data preparation through deployment and monitoring. I’m currently building Covality, a production ML system for spatial data-quality and anomaly mapping using Self-Organising Maps, with terrain-conditioned data valuation and model failure mapping.

I’ve also led applied ML work in academia, serving as Assistant Professor & Applied ML Lead at IIUM while directing 12+ initiatives across medical imaging, speech analysis, and signal processing, and mentoring 3 PhD and 7 Master’s students. As an independent ML builder and digital product developer (xariff.com), I founded and shipped 5+ production ML and full-stack web applications end-to-end, from architecture to CI/CD.

Experience

Work history, roles, and key accomplishments

Current

Independent ML Builder

Current

Xariff

Jan 2020 - Present (6 years 5 months)

Founded and delivered 5+ production ML systems and full-stack apps, owning architecture, deployment, and iteration across multiple verticals. Built Covality, an end-to-end spatial data-quality and anomaly mapping pipeline combining SOM spatial trustworthiness mapping with Isolation Forest anomaly detection and ML observability/reporting.

Self Organising Maps Isolation Forest PyTorch fastAPI Docker Redis GCP CI CD

Current

Assistant Professor & Applied ML Lead

Current

International Islamic University Malaysia

Jan 2016 - Present (10 years 5 months)

Led novelty detection and federated learning research funded by RM 63,000 FRGS and RM 103,800 FRGS grants, advancing applied ML for rare-event detection. Directed 12+ applied ML initiatives, supervised 3 PhD and 7 master’s students, and mentored 10+ junior researchers while building end-to-end Python/HPC ML pipelines.

Federated Learning Novelty Detection Anomaly Detection Speech Analysis Signal Processing Python HPC PyTorch

Education

Degrees, certifications, and relevant coursework

Universiti Malaya

Doctor of Philosophy (PhD), Particle Physics

Completed a PhD in Particle Physics. Thesis covered HPC and cloud-based machine learning for clustering and identification of novel high-energy physics reactions using unsupervised anomaly detection for BSM discovery.