What Does a Machine Learning Engineer Do?
Machine learning has changed the way we shop, watch movies and even drive our cars. Smart algorithms now power everything from Amazon’s product recommendations, to Netflix’s Watch Next choices, to which ads you see on your Instagram feeds.
Machine learning algorithms work by continually improving themselves the more data they take in. But these systems take skilled engineers to design, create and tweak them in order to deliver high quality data and results. So machine learning engineers are in constant demand by companies of all kinds.
What kind of work can you expect as a machine learning engineer? How much do machine learning engineers earn? And what do you need to do to prepare for a career as a machine learning engineer? Keep reading to find out.
What Does a Machine Learning Engineer’s Job Involve?
At first glance, machine learning engineers and data scientists may seem to have a lot in common. Both are tasked with designing systems to analyze and make sense of mountains of data. And data scientists at times use machine learning techniques to design algorithms to analyze data. But the similarities end there.
Machine learning engineers are essentially highly specialized software engineers. They are tasked with designing and coding the software that implements machine learning algorithms for specific applications. As software engineers, they may work as part of a team that both designs and builds machine learning software. As they gain more experience, they may take on senior roles that involve project management or Agile or Scrum team leadership.
Other machine learning engineers may work as consultants, helping other software developers to gain experience and insights about developing machine learning algorithms. Or they may advise businesses on how they can improve their products using machine learning.
Machine learning engineers — especially those who are leading teams — may interact with different stakeholders in order to deliver a completed product. This could include product managers, marketing and sales and executive teams. In those roles in particular, communication and collaboration skills are a must.
Where Can I Find a Job as a Machine Learning Engineer?
Machine learning engineers can find roles in many different companies. Well-funded Silicon Valley startups may be the first companies that come to mind — companies that make software-as-a-service (SaaS) products, as well as those on the cutting edge of new technology. Many startups are emerging that produce a physical product, not just software. This includes startups that are trying to create self-driving cars and manufacturing robots.
More mature tech companies that already use machine learning are also on the lookout for software engineering talent with machine learning experience. As we mentioned earlier, companies like Amazon and Netflix use machine learning to fuel their recommendation algorithms. And social media companies like LinkedIn and Facebook also use machine learning to decide what content to show to users. So programmers with knowledge of machine learning are in high demand.
Other industries are just starting to make use of machine learning to optimize their existing processes. For example, a manufacturing company may use machine learning to optimize their manufacturing process, their delivery routes, or their profit forecasting models. Or a bank or financial institution may decide to implement a machine learning fraud-detection system. So you may find a machine learning engineering role in an organization you may not expect.
How Much Can I Earn as a Machine Learning Engineer
Since the title “machine learning engineer” is a fairly new one, there isn’t a lot of reliable salary data yet. But according to the Robert Half 2020 Technology Salary Guide, other comparable roles like data scientists, data architects, and software engineers earn a median salary between $100,000 and $150,000 per year. So you can typically expect similar compensation as a machine learning engineer.
As with many software engineering jobs, the salaries for machine learning engineers vary by location. Major centers of tech growth, like New York and San Francisco, will offer higher salaries, while more rural or less tech-centric areas will have lower compensation levels.
What Skills Do I Need to Become a Machine Learning Engineer?
The most important skill for a machine learning engineer is programming. Since machine learning engineers are specialized software engineers, they will need to have a strong foundation in programming, application development, design, and other core software development skills.
The most popular programming language for machine learning is Python. It’s simple to get started with, but it has many powerful libraries available for data processing, algorithm design, and other key aspects of machine learning.
In addition to Python, machine learning engineers will need experience with other programming languages. Many in-house applications are written in Java or C++, so experience with those languages is a huge advantage. Additionally, there is a lot of math involved in machine learning. So skills in advanced mathematics and statistics is a plus — things like Bayesian statistics and linear algebra.
For working in a team environment, experience with Agile or Scrum development methodologies is often a requirement. This is especially true for startups and tech-focused companies, but more and more legacy companies are adopting these techniques for their in-house teams.
Since you’ll be working with data, machine learning engineers are expected to have some experience with data science. This includes data analysis techniques, data architecture, and advanced statistical models. While data science is a distinct field from machine learning, there can be a lot of overlap between machine learning engineering and data science, especially in smaller teams or in companies just getting started with either technology.
How Can I Learn Machine Learning?
Machine learning engineers often make the switch after having built up some experience as a more general programmer or software engineer. Others may specialize early on during their undergraduate or graduate studies. But if you’d like to learn more about machine learning without investing a lot of time and money, try the free SoloLearn Machine Learning course. In it, you will learn some of the most important concepts in machine learning, including linear regression, decision trees and neural networks. It’s taught using easy-to-learn Python, so even if you have limited experience with coding, you’ll be able to follow along in the course.
If you’re ready for a more advanced machine learning education, you can find free or low-cost machine learning courses available from top universities like Stanford and MIT. If you decide to take one of those courses, be sure to keep the SoloLearn app handy for review and practice anytime and anywhere.
Machine learning engineers also need strong data science skills. The SoloLearn Data Science with Python course is a great way to get up to speed on using frameworks like Numpy and Pandas to analyze large amounts of data.
You can also brush up on other programming languages through SoloLearn. C++ and Java courses can help you understand the most popular programming languages used by large corporations. This can help you become a more competitive candidate for machine learning engineer jobs within large companies.
In addition to the courses themselves, the SoloLearn community can help you to build your skills even faster. Join thousands of other learners on our forums to get answers to your questions and help others through their learning journey. Start learning today to launch your journey toward a career as a machine learning engineer!
