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Home Singapore Blog Machine Learning & AI Top Machine Learning Careers in Singapore: Roles, Skills & Salaries

Top Machine Learning Careers in Singapore: Roles, Skills & Salaries

Vamshi Krishna sanga by Vamshi Krishna sanga
October 28, 2025
in Machine Learning & AI
Top Machine Learning Careers in Singapore
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The Singaporean job market is witnessing a historic surge in demand for skilled Machine Learning (ML) professionals, thanks to the unprecedented growth of Artificial Intelligence (AI) over the past few years. According to Statista, the ML market is expected to grow at a CAGR of 29.8% by 2031.

This growth can be attributed to the Singaporean government’s initiatives and the widespread adoption of AI across sectors. These include healthcare, finance, e-commerce, and technology. 

This has thus contributed to the consistently surging demand for Machine Learning courses in the country. Take a look at some of the top career options for ML professionals in Singapore in this blog.

Source: Statista

Top Machine Learning Careers: Roles, Skills & Salaries

Some of the top career paths in Machine Learning for graduates with the relevant qualifications and skills include Machine Learning Engineer, AI Research Scientist, and Data Scientist, among others. Each of these roles varies by job responsibilities, required skills, and average earning potential.

To help you make an informed choice, the table below shares the top Machine Learning careers for eligible professionals. The corresponding salaries are also enumerated for easy reference:

Career RoleAverage Machine Learning Salaries (approx)
Machine Learning EngineerSGD 67,914 – SGD 94,000 per annum
Data ScientistSGD 120,000 – SGD 200,000 per annum
Deep Learning EngineerSGD 57,163 – SGD 108,233 per annum
Natural Language Processing EngineerSGD 99,443 – SGD 175,572 per annum
Computer Vision EngineerSGD 83,621 – SGD 148,187 per annum

Sources: Payscale, Morgan McKinley, Indeed, Salary Expert

1. Machine Learning Engineer

ML Engineers are software developers responsible for designing, building, and maintaining the systems and algorithms to enable computers to learn from data. They work with large datasets and are proficient in programming languages such as Python.

  • Translate theoretical models into strong, production-level software to be used in daily applications
  • Design and execute ML systems and algorithms with the ability to learn from data
  • Evaluate performance in production, optimise the models for improved accuracy, and initiate retraining with new data

Also read: AI Engineer Salary in Singapore

2. Data Scientist

Professionals who use a blend of statistics, programming, and domain knowledge to extract actionable insights from data are known as Data Scientists. They are skilled at working with both structured and unstructured datasets to solve complex problems.

  • Gather, clean, process, and validate large, complex data sets
  • Make use of ML and statistical techniques to build predictive models, identify patterns, and foresee outcomes
  • Convey findings and suggestions to the stakeholders for making strategic business decisions

Also read: How To Become A Data Scientist?

3. Deep Learning Engineer

They are specialists in designing, building, and deploying Deep Learning data models. They are a subset of Machine Learning using neural networks. Deep Learning Engineers are primarily responsible for developing models, engineering data, and deploying them into production.

  • Choosing, training, and optimising Deep Learning models using data frameworks such as PyTorch and TensorFlow
  • Defining the exact data requirements, gathering, cleaning, and labelling giant sets of data
  • Tracking evaluation metrics for optimal model performance 

Also read: 7 Innovative Approaches to Machine Learning

4. NLP Engineer

Specialising in Natural Language Processing (NLP), these professionals are responsible for designing algorithms for specific tasks. These include summarising text, analysing emotions, and creating chatbots.

  • Writing the required code for systems to process human language 
  • Build and train ML models for understanding language patterns and answering asked questions
  • Design and curate data sets used to train NLP models
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5. Computer Vision Engineer

A Computer Vision Engineer designs systems for enabling computers to understand and interpret visual data. These include images and videos. These professionals use ML and algorithms to design applications such as facial recognition, autonomous vehicles, and medical imaging systems. 

  • Clean, organise, and pre-process giant sets of data for model training 
  • Design and optimise ML models for classifying, detecting, and tracking objects in visual data
  • Integrate computer vision models into everyday applications for real-time analysis

Essential Skills for a Successful Machine Learning Career

Some key skills that can help build a rewarding and promising career path in Machine Learning include problem-solving, statistical analysis, and strong knowledge of NLP and other programming languages. All of these can help ML professionals chart a lucrative career path.

Some of the vital Machine Learning skills that can help you build a successful career in the field of AI/ML are:

Technical Skills

  • Strong understanding of Statistics and Mathematics for choosing and building models
  • Knowledge of handling data and analysing it for better understanding and interpreting data to derive valuable insights for improved decision-making
  • Proficiency in programming languages such as Python
  • Expertise in ML algorithms and Deep Learning networks
  • An understanding of ML libraries and frameworks like PyTorch, TensorFlow, and Scikit-Learn

Soft Skills

  • Practical verbal and written communication skills
  • Critical thinking and analysis
  • Problem-solving ability 
  • Teamwork and collaboration
  • Adaptability to the constantly changing technological landscape

Also read: Top Online AI ML Diploma Programs and Certifications for Job Opportunities

How upGrad Can Help You Build a Machine Learning Career

Machine Learning is the future of Singapore’s professional landscape. With fast-evolving AI/Me, you can now future-proof your career with professional, globally accredited courses on upGrad. These courses are fully online and offer the maximum flexibility to suit the work schedules of Singaporean professionals.

Some of the top offerings in the ML arena on upGrad include the ones from top international universities, such as:

  • Master of Science in ML and AI from Liverpool John Moores University
  • Executive Diploma in ML and AI from IIIT Bangalore

🎓 Explore Our Top-Rated Courses in Singapore

Take the next step in your career with industry-relevant online courses designed for working professionals in Singapore.

  • DBA Courses in Singapore
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View All Courses

FAQs on Machine Learning Careers in Singapore

What are the most popular Machine Learning careers in Singapore?

Some of the best in-demand career paths for ML professionals in Singapore include ML Engineer, AI Scientist, Data Scientist, and a few specialised roles in NLP and Computer Vision. 

How much does a Machine Learning Engineer earn in Singapore?

The average salary range for an ML Engineer in Singapore is estimated at SGD 67,914 to SGD 94,000 per annum (approx).

Do ML Engineers earn more than Data Scientists in Singapore?

   No, a Data Scientist generally earns more than an MLEngineer in Singapore. While Data Scientists earn SGD 120,000 – SGD 200,000 per annum, the average earning potential of ML Engineers ranges between SGD 67,914 and SGD 94,000 per annum.

How can I transition into Machine Learning from a non-tech background in Singapore?

One of the best ways to transition into an ML career from a non-tech background is to leverage your domain expertise and pursue practical ML training.

Can online programs help me land a Machine Learning job in Singapore?

Absolutely! Online courses offered on accredited platforms like upGrad are designed to enable working professionals in Singapore to land a rewarding ML job in the country. The course equips learners with the necessary professional skills in ML and related areas.

Vamshi Krishna sanga

Vamshi Krishna sanga

83 articles published

Vamshi Krishna Sanga, a Computer Science graduate with a master’s degree in Management, is a seasoned Product Manager in the EdTech sector. With over 5 years of experience, he's adept at ideating, defining, and delivering E-learning Digital Solutions across various platforms

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KEEP UPSKILLING WITH UPGRAD

Ushering the Era of Learning and Innovation
Back in 2015, upGrad’s founders noticed that the future of work demands industry professionals to upskill continuously – not just for their organization’s benefit but also for their personal growth. Earlier, learning would come to a halt as soon as professionals entered the workspace. upGrad brought along novel approaches towards imparting and receiving education by offering people a chance to upskill while working. We have always strived to facilitate quality education to the upcoming workforce through industry-relevant UG and PG programs.

Staying Dynamic and Forward-Looking
From being incepted in 2015 to teaching a learner base of 10k+ in 2018 to crossing the 1M mark in 2020 – upGrad has always focused on staying dynamic and future-centric. This approach has helped us grow as an organization while catering best-in-class learning to our students. In 2021, upGrad became a unicorn with a valuation of $1.2B, expanding to North America, Europe, the Middle East, and the Asia Pacific. Only onwards and upwards from here!

Growing and Expanding Constantly
Growth has been our true constant in this journey. Whether it is entering the unicorn club or winning the Best Career Planning platform award, or being ranked the #1 startup in India per LinkedIn’s 2020 report – we’ve always strived to go above and beyond our current capacities and bring novel ideas to the table for the betterment of learners across the globe. Join us in this revolution and help us impact more lives!

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