How to Become a Machine Learning Engineer

According to the Bureau of Labor Statistics, jobs in computer and information science are expected to grow by 16 percent by 2028, which they describe as “much faster than average.”

Machine Learning engineers command impressive salaries. According to Glassdoor, salaries for Machine Learning engineers range from $80,000 to $165,000, and the national average salary for Machine Learning engineers is almost $121,500.

However, there’s no way to know exactly how much you can expect to earn because Machine Learning engineer salaries depend on the company you work for and where you live. Machine Learning engineers in San Francisco earn an average of $140,500, whereas the same engineer in Seattle would earn $129,500.

1. Attend a short-term coding bootcamp specializing in data science.
2. Pursue a Computer Science degree at a college or university.
3. Learn data science through your own self-study.

Coding bootcamps offer a real alternative to a college education. Instead of spending four years in a university and taking on debt, aspiring coders can spend less than a year in a bootcamp learning everything they need to know to pursue a specific career in tech.

1. Statistics and Probability:

   You should be aware of various statistical analysis concepts such as distributions, median, variance and mean, and know how to use these concepts to learn from a set of data. You should also be aware of probability concepts like independence and conditional probability, which will come up in your work.

2. Data Modeling:

   Data modeling is at the core of Machine Learning. You should be able to model a dataset and find patterns within that dataset. You should also be able to evaluate the usefulness of a dataset and ensure that your algorithms will be functional based on available data.

3. Computer Science Fundamentals:

   Machine Learning engineering requires the use of a variety of fundamental computer science concepts. You should therefore understand topics such as queues, trees, arrays and stacks. You should also be aware of the main types of algorithms, such as sorts and searches, and understand the architecture behind a computer.

4. Python and R:

   Python and R are two of the most popular data science programming languages. You should be proficient in at least one or both of these languages and be able to use various libraries associated with them to analyze a dataset and implement a Machine Learning algorithm.

5. Software Engineering:

   As a Machine Learning engineer, you’ll need to know the basics of software engineering as well. You should be familiar with how different parts of software come together to create a final program. You should also be able to query a database, call an API, interact with a web service and overall, have a good understanding of how to interact with software and the web.

• Problem Solving:

  Coding is all about solving problems, so you should be a great problem solver. You should be able to break a problem down into smaller components, figure out different ways to approach them and come up with an efficient solution.

• Business Mindset:

  Your algorithms will be based on the needs of a business—you’ll receive a project specification and have to translate it into code. Thus, you should understand the goals of your client and get to know what they expect from their data analysis and Machine Learning teams.

• Iteration and Adaptability:

  Machine Learning is about trial-and-error, just like any other programming job. You’ll need to iterate in order to create a working program, and you’ll need to update your programs as more data becomes available and as the needs of a business change. You should be comfortable adapting to new specifications and iterating on your existing work.

1. Choose a Machine Learning engineering career path
2. Learn data science through a bootcamp, self-study or college
3. Develop and refine your technical skills
4. Build your Machine Learning portfolio
5. Write your technical resume
6. Start your job search
7. Prepare for an interview

We’ll also help you prepare for and get accepted to one of the top data science coding bootcamps so you can get the support and training you need to thrive in your new career.