How to get a machine learning job in Malaysia?

Feb 17, 2024


With the recent development of Generative AI, we now need even more machine learning engineers and specialists.

We need them to train the large language models (LLM) using Natural Language Processing (NLP), computer vision (CV), and analyze all other complex data.

In this blog post, I am going to share the career prospects of a machine learning engineer, and how you can find a machine learning job in Malaysia.

How much does a machine learning engineer earn in Malaysia?

The average salary of a machine learning engineer is RM 6,404 according to Indeed.

Average salary of a machine learning engineer in Malaysia by Indeed

Your salary varies depending on your experience, location, and the industry that you are in.

Junior Machine Learning Engineer

Salary range: RM 3,800 – RM 6,200 per month (Glassdoor)

A junior machine learning (ML) engineer helps a senior engineer with different ML jobs. These include gather data, extract features, train models, and check how well they work.

The senior engineer will lead the work, while the junior engineer puts together algorithms and creates models.

The junior engineer also tests how well the ML models work. They look for any issues in the models and find ways to improve them.”

Senior Machine Learning Engineer

Salary range: RM 4,800 – RM 8,500 per month (Jobstreet)

A Malaysian fintech company hiring senior ML engineers.


A senior machine learning engineer focuses on designing and developing machine learning systems.

They use algorithms to build machine learning models. Then, test the models and make sure they answer business questions.

A senior ML engineer must be good at data modeling, mathematics, and programming. You also need to have strong analytical and problem-solving skills.

As a senior, the company will expects them to lead and a team to tackle challenging issues and push forward innovations.

How to find a machine learning job?

Here’s a step-by-step guide to help you land a machine learning job in Malaysia.

Step 1: Research the job market

First, you need to understand what the employers are looking for.

Start by looking at job sites like Jobstreet, Indeed, and LinkedIn. Pay attention to the skills, qualifications, and experience.


Machine Learning Engineer job posting at Jobstreet


Building a professional network on LinkedIn can also be effective.

You can then learn from what other ML engineers are doing in their day job and industry best practices.

Step 2: Work on Projects

Next, put your knowledge into action.  Build some projects to gain practical experience.

The projects can be anything from predicting the sales for a grocery store to a program that recognises road signs. Try to build projects related to your industry.

Remember, the goal is to practice and learn.

Pro tip: Don’t use some toy datasets like Iris or the Titanic dataset, or build projects like recognising cats and dogs. Instead, go to open sites like Kaggle.com to find real datasets.


Find real-world datasets for different industries at Kaggle.com

Step 3: Build a portfolio

What is the best way to prove your skills?

Show, don’t tell.

Your future employer thinks so too.

So, instead of writing a long resume and cover letter that makes people sleep and most likely goes unread, why not create a portfolio that displays the projects you’ve worked on?

You can create a simple portfolio website using GitHub or WordPress. Remember to include details like what the project is for, how you did it, and what you have learned.

Your portfolio doesn’t need to be complex.

It could be as simple a single page with a few screenshots with descriptions, and then link it to your Google Colab notebooks.

Portfolio of Chris Low, a Data Science Uncut Bootcamp Graduate


Pro tip: Visit spaces.thelead.io and get inspirations from the portfolio of our past students.

Step 4: Apply for job and attend interviews

Here is a counter intuitive advice that will benefit you: 

Don’t just attend interviews for jobs that interest you. Attend as many interviews as you can.

This is to get you ready, understand the job market and questions that employer might ask.

With every interview you attend, you become more confident. Eventually you will be less nervous when you interview at your dream job.

You can also use interviews as an opportunity to gain feedback. Ask your interviewer about how well you fit the job, what other skills that you need, and use their feedback to improve.

Remember, each interview is a step forward in your job search journey. 

There could be many reasons if you didn’t  get hired,

It could be the skills, experience, or event culture fit. And all you need is just a job, so don’t get too desperate.

Other questions

Here are some of the questions you might have while looking for a machine learning job in Malaysia.

Is AI engineering in demand in Malaysia?

Yes, because AI is a fast-growing field in Malaysia.

In 2019, the Malaysian government launched the National Artificial Intelligence Roadmap, with the plan to develop and push AI technologies across various sectors.

The Malaysian AI ecosystem is also supported by a growing number of startups, research institutions, and accelerators.

As the AI ecosystem continues to mature, we can expect to see the demand of AI engineers continue to increase in the coming years.

Is machine learning a high paying job?

Yes, machine learning is a high-paying job. The median salary is RM 49,460 per year and can go up to RM 144,000 per year, according to Payscale.

Machine learning salary and bonus according to Payscale (2024)

Other roles that work with machine learning, such as data scientists, AI researchers, and AI engineers, are also typically high-paying jobs.

However, it’s important to consider factors other than salary when choosing a career, such as job satisfaction, work-life balance, and career growth opportunities.


Machine learning is a rapidly growing field in Malaysia, with many exciting career opportunities.

Whether you’re a fresh graduate or a seasoned professional who are looking for a career change, there are various ways to break into the machine learning industry in Malaysia.

By following the tips outlined in this blog, you can increase your chances of landing a job in this field.

Remember to build a strong foundation in the relevant skills, both technical and soft skills.

Stay up to date with the latest developments in the field by attending conferences and meetups, and connect with other professionals in the industry.

A solid certification can further enhance your skills. You may also check out our Data Science 360 flagship program, a proven program that has helped thousands of students to kickstart a data and machine learning career.

Finally, don’t be afraid to reach out to companies directly and inquire about potential job openings.

With the right skills, knowledge, and networking, you can land a job in the exciting field of machine learning in Malaysia.

Good luck in your job search!

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