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Image of career: Artificial Intelligence/Machine Learning (AI/ML) Engineer

Artificial Intelligence/Machine Learning (AI/ML) Engineer

Overview

Artificial Intelligence/Machine Learning (AI/ML) engineers build the brains of modern technology. Create machine learning systems, develop algorithms that can predict what happens next, and design self-improving AI software.

Description

  • Build smart systems that can predict future outcomes.
  • Conduct experiments, testing, and statistical analysis to validate model performance.
  • Choose the right algorithm for problem-solving.
  • Analyse data and improve existing AI tools and frameworks.
  • Train AI systems to learn and improve their performance.

Entry requirements

  • You'll need at least a Bachelor's Degree in Computer Science, Engineering, or something similar.
  • It’s also beneficial to be familiar with deep learning frameworks like TensorFlow, PyTorch, MXNet and Microsoft Cognitive Toolkit.

Salary

$6,000 – 11,000

/mo

Salary ranges are estimated based on public information found on Singaporean job portals, including MyCareersFuture, MySkillsFuture. Updated as of 2026.

Trivia

Ever notice how Instagram shows you exactly the stuff you're interested in? That's AI/ML at work. Social media platforms use AI/ML tools to learn what you like, then show you targeted ads that might influence what you buy.

What to expect

The industry is growing quickly and constantly changing. There are always new tools, updates, and concepts to learn.

Soft
skills

Communication

complicated tech concepts in simple terms.

Collaboration

Able to work in teams with data scientists, programmers, and business.

Problem-Solving

Ability to create smart algorithms and innovative models to solve challenges.

Statistical Skills

Able to work and grapple with numbers, probabilities, and data patterns to understand information.

Programming Languages

Skilled in coding languages like Python, R, or Java.

Data Science

Ability to discover insights in large datasets using specialised data tools and techniques.

Hard
skills

Frequently asked questions

Think of it this way - AI/ML engineers build the AI systems, while data scientists study data to find insights that help companies succeed.

Almost anywhere. AI/ML is booming across all industries. Big tech companies like Google, Apple, and Amazon offer many exciting AI/ML career opportunities.

Engineers use techniques like cross-referencing to ensure the AI deliver consistent, reliable results.

One key method is checking data quality - engineers carefully examine all the information used to train the AI to make sure it's accurate and trustworthy.

Engineers use many tools, including programming languages like Python and Java, along with machine learning tools like TensorFlow to build and train AI systems.