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How to Become a Machine Learning Engineer in 2024?
Published
22nd Dec, 2023
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Machine learning is a subset of artificial intelligence, which stresses the analysis and identification of patterns and structure of data interpretation. This helps in reasoning and efficient decision-making that is backed by strong evidence.
At present, data is the backbone of all businesses. The use of ML can help to analyze the humongous amounts of data and arrive at conclusions that are in favor of both customers as well as businesses. With the rising demand for machine learning technologies in almost all sectors, there is also a soaring need for experts who are skilled in this field. This article answers all your questions on how to become a machine learning engineer. Read on to find out.
Who is a Machine Learning Engineer, and What Do They Do?
A machine learning engineer is a professional who develops and refines the algorithms which are further used by machine learning tools. This helps to execute the tasks without human interference and allows the computers to analyze past trends and predict future events.
Machine learning engineers have to work in collaboration with data scientists and computer scientists, who have the skills to solve complex problems with great ease and transform data so that organizations can make better decisions.
Some of the responsibilities of machine learning engineers are as follows:
- The primary task of machine learning engineers is to design and develop the models of ML systems.
- They have to choose the most appropriate datasets for analysis before proceeding with the modeling. They also analyze the accuracy of the models being used or suggest improvements as and when required.
- A machine learning engineer has to figure out the differences in data distribution, which can further lead to errors in model performance.
- He performs data visualization to gain deeper insights. He also verifies the quality of data to make sure that the results obtained are accurate.
- A machine learning engineer also analyzes the cases where the ML algorithms are being used and determines the success probability of using each.
However, the roles and responsibilities may vary from one organization to another based on the requirements. Acquiring a Data Science course online can help you keep up with the changing trends while helping you advance in your career.
The next step discusses how to become a machine learning engineer in just a few steps.
How to Become a Machine Learning Engineer? [In 5 Simple Steps]
You can still work your way towards a career in machine learning engineering. Discussed below are a few steps on how to become a machine learning engineer.
Step 1: Master Skills
It takes an individual to have command over soft skills, hard skills, and other competencies to be able to become a successful machine learning engineer.
A. Top Skills Needed to Become a Machine Learning Engineer
1. Soft Skills: Machine learning engineers should have great interpersonal abilities and should be able to connect well with all the stakeholders, both internal and external. He should also have great analytical skills. Apart from these, time management and leadership skills are also considered important.
2. Hard Skills: Hard skills refer to the technical skills that a machine learning engineer should have knowledge about. Knowledge about the following topics can give you an edge over others.
- Knowledge of Applied Mathematics: Machine learning has algorithms for data analysis, which can be applied with the help of mathematical formulas. Mathematics makes it easier to set approximate levels of confidence and other parameters. Some of the most important mathematics topics that you should know are statistics, probability, linear algebra, etc.
- Fundamentals of Computer Science and Programming: This is another requirement that will help you emerge as a successful machine learning engineer. You should be knowledgeable about the different concepts of computer science, such as data structures like tree, queue, stack, graph, etc., space and time complexity, and algorithms like sorting, searching, etc.
- You should also be proficient in using different programming languages such as Python and R. Other technologies, such as SQL, Apache Kafka, Hadoop, etc., also help with database management, pre-processing of data, and distributed computing, respectively.
- Python is used for ML and data science; therefore, it will be ideal if you are knowledgeable about libraries like Pandas, NumPy, Matplotlib, etc.
- Data modeling and evaluation- Data modeling refers to the understanding of data structure and finding the pattern, which may not be visible to someone who isn’t skilled in the sphere. You also should be able to understand the different machine learning algorithms to be able to execute the task of data modeling and evaluation in a seamless manner.
- Natural language processing (NLP)- Natural language processing is a concept in AI and computer science that has the ability to translate texts from one language to another. NLP equips computers with the ability to comprehend text as well as spoken language.
3. Other Competencies: Alongside the hard and soft skills mentioned earlier, an aspiring machine learning engineer should have other competencies like good team management skills, prompt decision-making abilities, creativity, and a calm temperament.
B. Top Machine Learning Certifications / Degrees
You may be wondering how to become a machine learning engineer without a degree. A certificate helps to verify your skills in a specific domain. If you want to establish your career as a machine learning engineer, you can pursue some relevant courses that will help you validate your knowledge.
The following degrees or certifications will pave your career path to becoming a machine learning engineer:
- An undergraduate degree: Knowledge of mathematics, computer science, data science, and computer programming help to build a strong foundation for individuals who are wondering how to become a machine learning engineer after 12th. Alongside these, degrees in fields like physics and statistics are also beneficial.
- Post graduation: After you have completed your undergraduate course, you can enroll for a master’s degree in the relevant discipline.
- Domain-specific certification course: If you are wondering how to become a machine learning expert, here is some news for you. Niche-specificity helps you strengthen your skills in a given domain. By enrolling in KnowledgeHut's Data Science course online, you can gain a competitive advantage by earning a certification.
Step 2: Determine Your Ideal Timeline
It takes time to reach somewhere. If you set a timeline, it will pave the way to a smooth completion of your preparatory phase so that you are ready to assume the role.
A. Start Learning in a Format That Suits You
There is “no one size fits all” when it comes to choosing learning formats. Learners adapt to different learning styles. While some learners prefer a visual mode of instruction, others respond to verbal instructions better. Therefore, choose the format that suits you the best.
B. How Long Does It Take to Become a Machine Learning Engineer?
Based on your learning pace, you may require somewhere a couple of years to acquire the relevant skills and degree. However, since it is not an entry-level post, one should have the required experience to be able to deal with the responsibilities that this post bears.
Step 3: Begin Building Your Portfolio / Resume
Your resume is a representation of your skills and knowledge. While a resume gives concise information about the skills you possess, your qualification, and your work experience, a portfolio allows you the provision to showcase your work experience in detail with the help of examples.
Portfolio Example or Resume Template for Download
It is important to build your resume as attractive as possible. Make sure it highlights your strengths and arrests the immediate attention of the recruiters.
Download Machine Learning Engineer resume template here!
Step 4: Where and How to Find a Job
An important aspect of “how to become a machine learning engineer” is looking for the most suitable job prospects. It is important to leverage your professional network and earn as much visibility as possible. Some online certification courses also offer placement support to learners.
A. Top Companies Hiring Machine Learning Engineers
In order to keep up with the cutthroat market competition, companies have to make data-driven decisions. Renowned companies like Amazon, Accenture, TCS, Wipro, Capgemini, Microsoft, etc., hire machine learning engineers.
B. Job Outlook for Machine Learning Engineers
If you are worried about how to get a job as a machine learning engineer, remember that ML engineering opens up a wide horizon of opportunities for candidates. If you pursue ML engineering, you will be able to secure a position in industries like manufacturing, diagnosis and medical testing, customer service, cybersecurity, agriculture, retail, advertising, and many more.
If you have a background in ML, you can also assume other roles such as NLP scientist, data scientist, business intelligence developer, research scientist, etc. Therefore, if you are adept in AI, enjoy coding, and have good problem-solving abilities, you will be able to carve a fulfilling career.
Step 5: Ace the Interview
While your resume will showcase your skills, a job interview will reveal your personality. Candidates can exhibit skills like good communication, honesty, a positive attitude, and active listening to mold the recruiter’s decision in their favor.
Brief Overview of Interview Process + Tips
To ace the interview process, you will have to look for the companies where you wish to work. After that, browse through the company details thoroughly. You should also be thoroughly informed about the job description.
Revise your resume in depth and recall all the examples that you will cite from your work experience. Try practicing a few rounds of interviews with your peers.
Last but not least, be confident. Your body language leaves a huge impact on the recruiters.
Who Can Become a Machine Learning Engineer?
Machine learning is a complex technology that uses AI and other advanced technologies, such as Data Science. To become a machine learning engineer, there are a few skills that you need to pre-possess.
Machine Learning Engineer Requirements/Prerequisites
Now that you have an idea about how to become a machine learning engineer, here are some prerequisites that might be preferable. Having command over some subjects and topics can prove to be an added advantage if you are looking forward to becoming a machine learning engineer.
For anyone who is wondering how to become a machine learning engineer, it is first important to gain knowledge about web development, statistics, mathematics, data science, computer science, programming languages, and libraries to work with.
While it is a commendable skill to understand data and the messages delivered by the data patterns, it is equally important to convey these valuable insights effectively so that the shareholders, clients, and other non-technical staff too can use this information.
Benefits / Why Become an ML Engineer?
Along with “how to become a machine learning engineer,” career enthusiasts also look for answers to questions like “why one should become a machine learning engineer.” Not only does the career option offer lucrative packages, but it is also in high demand. It gives you the opportunity to work with the latest technologies, and there is ample scope for learning.
A. What’s the Demand for Machine Learning Engineers?
The use of ML has found its way into many industries. As technology is growing complex, there is an increase in demand for professionals skilled in handling data and proficient in using advanced AI and ML technologies.
B. Salary Details for Top 5 Countries
Machine learning engineering is a rewarding job. Listed below are the top 5 countries that are adept in using ML technologies and hiring ML engineers for the same.
| Country | Salary |
US | USD 110,098 per annum |
UK | GBP 63,070 per annum |
China | CNY 65,070 per annum |
Australia | AUD 126,146 per annum |
Canada | CAD 105,558 per annum |
Conclusion
Hope this gives you an idea about how to become a ML engineer. If you are willing to kickstart your career as a machine learning engineer, you can pursue Machine Learning courses offered by KnowledgeHut. This will equip you with the ability to use data effectively and contribute to an organization’s future decisions and goals. This will equip you with the ability to use data effectively and contribute to an organization’s future decisions and goals.
Frequently Asked Questions (FAQs)
1. Where Do Machine Learning Engineers Work?
Machine learning engineers work in a number of industries like healthcare and diagnosis, cybersecurity, retail and customer service, manufacturing, advertising, etc.
2. What Does a Machine Learning Engineer Do?
A machine learning engineer has to work with enormous amounts of raw data. He has to devise and implement the ML algorithms that will process the data.
3. What qualifications do I need to be a machine learning engineer?
If you are wondering ‘how do i become a machine learning engineer’, you will first need to have a bachelor’s degree in any of the relevant fields like computer science, statistics, mathematics, etc. An advanced course in a specific domain helps to enhance your skills and increases your chances of being recruited.
4. How long does it take to become a machine learning engineer?
If you are wondering ‘how to get machine learning job without experience’, the answer is that it is very hard to do so. Since an ML engineer is not an entry-level position, it takes years of skill, knowledge, and experience to become a machine learning engineer.
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