How to Become a Machine Learning Engineer
Step 1: Understand the job description and responsibilities of a Machine Learning Engineer
What does a Machine Learning Engineer do?
A Machine learning (ML) is the scientific study of algorithms and statistical models that computer systems use to effectively perform a specific task without using explicit instructions, relying on patterns and inference instead. It is seen as a subset of artificial intelligence. Machine learning algorithms build a mathematical model of sample data, known as "training data", in order to make predictions or decisions without being explicitly programmed to perform the task.:2 Machine learning algorithms are used in a wide variety of applications, such as email filtering, and computer vision, where it is infeasible to develop an algorithm of specific instructions for performing the task. Machine learning is closely related to computational statistics, which focuses on making predictions using computers. The study of mathematical optimization delivers methods, theory and application domains to the field of machine learning. Data mining is a field of study within machine learning, and focuses on exploratory data analysis through unsupervised learning. In its application across business problems, machine learning is also referred to as predictive analytics.
The diversity of machine learning programs demonstrates nothing but the growing demand for machine learning engineers.
And if you look at a similar report from the popular job portal Indeed, the job opportunities in the spectrum of AI have doubled over the last 3 years with the most in-demand job roles being Machine Learning Engineers, Deep Learning Engineers, and Data Scientists.
Yes, machine learning engineers deal a lot with math, numbers, and algorithms.
But there’s much more to the machine learning engineer job role than that.
Keep reading to find out whether a machine learning engineer job could be your future job title.
Step 2: Learn best tips to become a Machine Learning Engineer
Best tips for those who want to become a Machine Learning Engineer
Here are some tips to become a Machine Learning Engineer.
Those that are focused a lot on analytics.
Those focused more on algorithms and machine learning.
Earn a master’s degree and/or Ph.D.
develop a competitive compensation package.
identify the top skills for machine learning engineers.
Step 3: View best colleges and universities for Machine Learning Engineer
Best colleges and universities for Machine Learning Engineer
- Butler University
- Carroll College
- Cooper Union
- High Point University
- Princeton University
- Providence College
Step 4: Think about whether is it worth to be a Machine Learning Engineer
Is being a Machine Learning Engineer Worth it?
- Experience in developing a machine learning algorithm utilizing Python (Keras, Tensorflow, scikit-learn, matplotlib, Pandas, NumPy etc.).
- Extensive knowledge in NLP, machine learning and mathematical and statistical analysis - Experience in information dissemination/ deployment in the artificial intelligence field, statistical analysis and machine learning (published papers, technical reports or any experience in being published).
Machine Learning Engineers are high-level computer programmers who specialize in applying the principals of Artificial Intelligence (AI) to enable machines to learn and then carry out tasks they have not been specifically pre-programmed to perform.
The educational and job requirements employers are typically looking for in a machine learning engineer candidate include a master‰Ûªs or doctoral degree along with advanced skills in computer programming, mathematics, cloud applications and computer languages.
Machine Learning Engineer has launched a new guide to available online courses in machine learning and deep reinforcement learning.
Step 5: Prepare relevant skills for being a Machine Learning Engineer
What skills do you need to be a Machine Learning Engineer?
This is not a management position, but still requires important skills in order to fully execute the role. A keen understanding of the following is necessary for the role: Code Optimization, Code Refactoring, Debugging, Programming, Software Architecture, Software Development, Software Development Lifecycle (SDLC), Software Integration Engineering. Some of the more basic skills utilized in this role include: Application lifecycle management (ALM) Software, Bug Tracking Software, Integrated Development Environment (IDE) Software, Source Code Management Software, Programming Language. These skills are certainly important to the role, but keep in mind, fit into a company culture and environment is often just as important.
Andrew Ng’s Machine Learning (and his more up-to-date Deep Learning specialization) are great starting points.
Bear in mind, these are mainly the skills you would need to meet the minimum requirements for any machine learning job.
For engineers experienced in linux or MacOS command line this may not be required.
As more organizations begin to explore and invest in machine learning and artificial intelligence, they’re looking to hire more experts to integrate these technologies into their business initiatives.
For programmers wishing to switch to machine learning engineering, you’ll need experience with big data sets.
Step 6: View average salary for Machine Learning Engineer
How much does a Machine Learning Engineer make?
The average salary range for a Machine Learning Engineer is from $96,328 to $114,994. The salary will change depending on your location, job level, experience, education, and skills.
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Average salary for Machine Learning Engineer jobs
Step 7: Find relevant Machine Learning Engineer jobs, and apply.
Looking for Machine Learning Engineer jobs?
Here are some Machine Learning Engineer jobs in the United States.