Engineering training environment

// About cindras

Training Engineers to Work
With the Hardware, Not Around It

cindras was built on the conviction that ML engineering education should reflect the realities of production systems — including the hardware those systems run on.

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// Our Story

Where cindras Came From

cindras started in Cyberjaya in 2019 when a group of engineers who had spent years working on deployed ML systems noticed a recurring gap in the people coming through standard training channels. The programmes available taught frameworks well enough, but left engineers unprepared for the conversations that came up the moment they had to think about compute budgets, memory constraints, or why a model that ran fine on a workstation was struggling in production.

The founding team — who had backgrounds spanning semiconductor work, systems programming, and applied research — decided to build a programme where hardware was not an afterthought but a lens through which every topic was introduced and examined. The first cohort ran with twelve participants. By 2022, cindras had delivered training to teams from organisations across the Klang Valley and Penang.

Today, cindras offers three structured programmes: an entry-level foundations course, an applied engineering track for practitioners ready to go deeper, and a corporate cohort service for organisations upskilling teams. The core commitment has not changed — to training that reflects the workbench, not just the textbook.

// Mission & Values

What We Stand For

Engineering Discipline

Every programme is designed to build the kind of methodical thinking that engineering work demands — not shortcuts, but durable understanding.

Practical Before Abstract

Theory earns its place by explaining what participants already encountered in a lab. We introduce concepts through problems, not before them.

Honest Scope

We are specific about what each programme covers and what it does not. Participants know what they are working towards before they start.

Rooted in Malaysia

cindras is built for the Malaysian engineering community — the examples, the industry context, and the peer network are local by design.

// The Instructors

The People Behind the Programmes

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Azrul Rashid

Lead Instructor — Systems

Former semiconductor engineer with eight years in compute architecture. Leads the hardware curriculum across all cindras programmes.

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Shivani Nair

Instructor — Applied ML

Applied ML practitioner with a background in model deployment pipelines. Leads lab sessions and project work for the Applied Engineering Track.

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Lim Kah Wai

Programme Coordinator

Coordinates corporate cohort planning and participant support. Ensures programme schedules, materials, and logistics run as designed.

// How We Work

Our Standards and Approach

Structured Curriculum Review

Programme content is reviewed and updated on a regular basis to reflect changes in hardware tooling and ML engineering practice.

Participant Data Privacy

Enrolment data and correspondence are handled in accordance with Malaysia's Personal Data Protection Act 2010 (PDPA).

Lab Environment Quality

Lab environments and sample datasets are tested before each programme run to confirm they reflect current engineering conditions.

Post-Programme Feedback

Each programme concludes with a structured feedback process. Responses are reviewed by instructors and used in subsequent curriculum planning.

Practitioner-Led Delivery

Instruction is delivered by engineers with active professional backgrounds in the topics they teach — not contracted trainers unfamiliar with the material.

Documented Programme Scope

Every programme has a written scope document shared with participants before enrolment so expectations are clear from the start.

// Our Expertise

Engineering Training Built on Production Experience

cindras's programmes sit at the intersection of machine learning and hardware engineering — a pairing that is increasingly important as ML systems move from research settings into deployed products. Engineers who understand memory bandwidth, compute utilisation, and data movement write better code, make better architecture choices, and collaborate more effectively with the infrastructure teams who keep those systems running.

The Malaysian engineering market has seen a marked increase in demand for ML skills across sectors including fintech, manufacturing, and telecommunications. cindras's programmes are designed to serve developers already working in these environments — people who need to go further with ML but cannot afford to lose the hardware instincts their day jobs have given them.

Participants in cindras programmes come from software development, data engineering, and systems administration backgrounds. What they share is a willingness to sit at a workbench, work through problems carefully, and leave with an understanding they can apply the following week at their job. That is the standard cindras programmes are built to reach.

// Join cindras

Find the Right Programme for Your Path

Individual developers and engineering teams are welcome to get in touch. We will help you identify the right starting point.

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