How to become a Machine Learning Engineer
Machine Learning Engineer
Machine learning is a branch of artificial intelligence that gives technology the power to teach itself; and machine learning engineers create the programmes and algorithms for these technologies to operate.
Machine learning engineers create technologies that can function with minimal human involvement. They make programmes and algorithms to not only instruct technology to do something, but to also learn from itself.
These technologies will remember when they have done something correct and learn it for next time, so they will be able to repeat the procedure. An example of machine learning is algorithms for websites like YouTube; suggested videos are shown to the consumer, who gives feedback to the algorithm by watching or hiding these videos.
Machine learning engineers also work with artificially intelligent products like self-driving cars or robots. They program these technologies to not only run without human interaction, but to correct themselves after mistakes.
There is no machine learning engineer degree, but most people in this role will have a masters or higher in a related subject, such as computing or mathematics. Because this is a very new career, machine learning engineers often come from a data science and programming background.
To become a machine learning engineer, you should also develop these skills:
- Excellent statistical knowledge, so they can make calculated predictions regarding what might happen with their technologies in ‘the real world’.
- Other applied mathematical knowledge including advanced algebra and calculus.
- Advanced knowledge of coding languages, such as Python, R, Java and C++.
- Signal processing techniques, like time-frequency analysis and advanced signal processing algorithms.
- Software engineering, as it is very important that machine learning engineers know how the parts of each technology work together.
The machine learning engineer salary is high, but the role is one that requires a lot of training and education. Machine learning engineers are in high demand; this is because the increase of use in technology results in a natural correlative increase of data. It would be near impossible for a human to go through this and create tailor-made programmes for consumers; teaching technology to do so is a much more productive use of time.
What degree is most commonly held by a Machine Learning Engineer?
- Master of Computer Science
- Master of Mathematics
- Master of Artificial Intelligence
- Master of Data Science
- Master of Physics
- Master of Computer Engineering
- Master of Electrical and Electronics Engineering
- Master of Machine Learning
Career Transportability across Countries
What skills are needed to become a Machine Learning Engineer?
- Machine Learning
- Data Analysis
- Deep Learning
- Software Development
- Python (Programming Language)
- Microsoft Office
- Data Science
- Data Mining
- Microsoft Excel
Machine Learning Engineer Courses
- Introduction to Creative AI
Explore the ways AI is changing the creative industries and how you can develop your own career in creative AI
- Advanced Machine Learning
Improve your understanding of machine learning Explore advanced techniques and how to use them in your data science projects
- Big Data: Statistical Inference and Machine Learning
Learn how to apply selected statistical and machine learning techniques and tools to analyse big data
- Apply Creative Machine Learning
Discover the creative side of machine learning with this free course using hands-on examples
Machine Learning Engineer Microcredentials
- Artificial Intelligence on Microsoft Azure: Machine Learning and Python Basics
Develop AI and machine learning skills using Python and Microsoft Azure on the path to rolebased certifications
- Advanced AI on Microsoft Azure: Ethics and Laws, Research Methods and Machine Learning
Explore the ethics and laws surrounding AI and develop advanced AI and machine learning skills using Python and Microsoft Azure
Need even more evidence about why you should learn on FutureLearn?
Introduction to Creative AIExplore the ways AI is changing the creative industries, and how you can develop your own career in creative AI.Show course overview
Advanced Machine LearningImprove your understanding of machine learning. Explore advanced techniques and how to use them in your data science projects.Show course overview
Big Data: Statistical Inference and Machine LearningLearn how to apply selected statistical and machine learning techniques and tools to analyse big data.Show course overview
Apply Creative Machine LearningDiscover the creative side of machine learning with this free course using hands-on examples.Show course overview