Machine Learnin
A machine learning engineer is an engineer that uses programming languages such as, Python, Java, Scala, etc., to run experiments with the appropriate machine learning libraries. To describe in more detail, Tomasz Dudek says it well:
“… a person called a machine learning engineer asserts that all production tasks are working properly in terms of actual execution and scheduling, and abuses machine learning libraries to their extremes, often adding new functionalities. (They) ensure that data science code is maintainable, scalable, and debuggable, automating and abstracting away different repeatable routines that are present in most machine learning tasks. They bring the best software practices to the data science team and help them speed up their work…”
By no means is this career limited to tech-focused businesses though. Machine learning can be applied in many industries working with large amounts of data, including financial services, retail, government, healthcare, transportation, and even oil and gas. By gaining, often real-time insights, from this data, these industries are able to work more efficiently and even gain an advantage over their competitors. Because of the wide variety of industries, “machine learning engineer jobs grew 344% between 2015-2018,” according to Forbes.
What is the career path for a machine learning engineer?
To become a machine learning engineer, you typically have to work your way up so you have enough education and work experience under your belt. Here’s a guideline to follow:
1. Complete your undergraduate degree
Acceptable degree options are math, data science, computer science, computer programming, statistics, or physics. An understanding of business is also helpful.
2. Entry-level careers
You typically can’t jump into a career as a machine learning engineer so some places to start are as a software engineer, software programmer, software developer, data scientist, or computer scientist.
3. Earn your master’s degree and/or PHD.
The majority of machine learning engineer jobs require more education than an undergraduate degree. Aim to receive a master’s degree in data science, computer science, software engineering, or even a PHD in machine learning.
4. Keep learning
A career as a machine learning engineer means that your education never ends. As technology continually grows, your need to always be researching AI and understand new technologies becomes even more important. A great deal of leadership skills is also useful.
Fact: Not all organizations can justify a full-time machine learning engineer, so a career as a freelancer is also a good option.
Skills Required:
- Programming
- Probability & statistics
- Data modeling
- Machine learning algorithms
- System design
Salary Range: $69,000-$150,000+ depending on experience level.