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How to Become a Machine Learning Engineer - Complete Career Path

How to Become a Machine Learning Engineer - Complete Career Path

Machine Learning is an application or subset of Artificial Intelligence (AI). Machine Learning is among the most powerful and highly influential technologies today. This technology helps instill the ability to learn and function in machines and computer systems without the need for any human supervision.

This blog covers the following topics:

Check out this YouTube video to get a better understanding of Machine Learning:

Before talking about how you can become a Machine Learning engineer, let us begin this blog by understanding what is Machine Learning.

A Step-By-Step Guide

What is Machine Learning?

Machine Learning allows systems to learn and improve from past data and experiences without having to be programmed. It generally focuses on the overall development of numerous computer programs to make them capable of accessing and processing large amounts of business data using Machine Learning techniques and Deep Learning algorithms, which is a significant concept and subset of Machine Learning.

Machine Learning Process

Machine Learning helps machines analyze and identify patterns from historical datasets, and on the basis of that data, these systems learn to make classifications and decisions without any human supervision. Similar to how humans learn from their experiences and make improved decisions, Machine Learning trains computer systems to gain knowledge from pre-existing data to perform better in the future.

Machine Learning differs a lot from the old and traditional programming methods. Traditional programming requires humans to feed necessary data into the system and build codes and programs to transform this data into the required output. Traditional programming requires a lot of human involvement and is also limited to the human abilities of structuring data and defining it.

In Machine Learning, data needs to be fed into the system, and on the basis of the earlier fed data, the system builds up its logic to get the desired result. In this process, the system is developed to learn without any human intervention or guidance.

machine learning process

Almost every industry makes use of Machine Learning concepts and applications. It is extensively adopted by social media networks to build an enjoyable and more customized user experience. However, Machine Learning has other practical applications as well in the fields of telecommunication, video surveillance, healthcare, and more.

As per McKinsey & Company, a leading consulting firm, Machine Learning will generate more than US$100 billion annually in just healthcare.

Looking to get started with Machine Learning? Read our guide to learn about the Prerequisites for Machine Learning.

What does a Machine Learning Engineer Do?

A Machine Learning engineer is a programmer who builds systems and machines that have the ability to learn as well as apply the gained knowledge without being specifically programmed. They develop codes and programs that allow machines to take necessary actions in particular situations.

The engineers generally work with Big Data. They feed business data into models that are designed by data scientists. They are also responsible for adapting various theoretical models of Data Science and sending them for production so that they can handle large amounts of real-time data.

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How to Become a Machine Learning Engineer?

You can take the following steps to become a Machine Learning engineer:

  • Have a vision about a Machine Learning career
  • Learn the fundamentals of Software Engineering
  • Learn Data Science
  • Learn the tools and concepts related to Machine Learning
  • Build projects
  • Do a course in Machine Learning

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Have a Vision About a Machine Learning Career

To get the best out of a Machine Learning career, you must first be clear about your end goal. Basically, you must first figure out what you want out of a career in Machine Learning. This self-study is required so that you can aim for the best career path for you.

Each role in Machine Learning requires a different set of qualifications and degrees. For example, some Machine Learning careers require a bachelor’s degree in statistics, mathematics, or related fields. On the other hand, some careers may require you to have a master’s degree in a specific domain. However, in many cases, your job role and work experience also give you weightage. So, to summarize, you need to first understand the direction you wish to take in the domain of Machine Learning.

Learn the Fundamentals of Software Engineering

As a Machine Learning engineer, you will need to write codes that would run systems and programs. So, it becomes very important to learn the fundamentals of software engineering, which involves programming languages. To aim for any role in Machine Learning, you need to be well-versed in popular programming languages such as Python, Java, C++, etc.

Learn Data Science

In the majority of the cases, the role of a Machine Learning engineer overlaps with that of a data scientist. A skilled ML engineer not only has knowledge of Machine Learning but also of Data Science. As they must be able to perform Data Science actions such as cleaning, optimizing, finding, querying, and understanding everything there is to know about data models. You must know how to combine the concepts of Software Engineering and Data Science to arrive at adequate solutions and findings.

Enroll in this Online M.Tech in AI and ML by IIT Jammu to enhance your career!

The Machine Learning infrastructure involves not only programming languages and Software Engineering tools and techniques but also certain Data Science and Machine Learning tools. So, as a Machine Learning engineer, you must be prepared to use tools such as TensorFlow, R, Apache Kafka, Hadoop, Spark, and PySpark, etc.

Build Projects

You will be completely prepared to start a career in Machine Learning only when you are well equipped to deal with real-life scenarios. Hence, you must start with applying the theoretical knowledge to real-life-based Machine Learning projects. You must carry out an entire Machine Learning project from start to finish. This will also go a long way in building your ability and showcasing your skills to future employers.

Do a Course in Machine Learning

You should enroll in a Machine Learning course to be adequately equipped with all the required concepts in Machine Learning as well as related Data Science fundamentals. Having a certificate also validates your skills and shows your experience in the domain to prospective employers.

Read more – Best Programming Language for Machine Learning

Machine Learning Engineer Skills

Some of the necessary skills that you need to acquire to become a Machine Learning Engineer are as follows:

  • Experience in programming languages such as C++, Python, Java, or R
  • Understanding of probability and statistical concepts
  • Knowledge of applied mathematics along with algorithms and models
  • Basic understanding of distributed computing
  • Work experience in at least one UNIX tool
  • Knowledge of Hadoop and its numerous applications
machine learning engineer skills

Go through these Machine Learning Interview Questions for Freshers to crack your interviews.

Now, let us discuss the various roles and responsibilities of a Machine Learning engineer.

Roles and Responsibilities of a Machine Learning Engineer

Some of the major roles and responsibilities of a Machine Learning engineer include:

  • Making use of the fundamentals of computer science such as algorithms, data structures, complexity, and computer architecture
  • Using numerous mathematical skills to perform calculations and computations and to work with algorithms based on programming
  • Producing project results and isolating resolution-requiring problems to bring more effectiveness in codes and programs
  • Collaborating with data to develop various data model pipelines
  • Managing data pipelines and infrastructure to produce a code
  • Creating algorithms on the basis of various statistical models and processes
  • Making use of data evaluation and data modeling strategies to identify patterns and depict future instances
  • Applying relevant Machine Learning libraries and algorithms
  • Analyzing large and complex sets of structured and unstructured data to gain insights and decide techniques
  • Researching and further implementing the latest techniques and practices to improve organizational infrastructure

Now, let us get an overview of the hottest job opportunities available in this field.

Also, check our blog on Cost Function in Machine Learning!

Why Should You Learn Machine Learning?

In this digital era of Machine Learning and Artificial Intelligence, at every turn, you will see these technologies surrounding you. For economic and technological growth, the future will be filled with Artificial Intelligence devices around the world. Due to this, numerous companies across all industries are adopting these technologies. So, they will require Machine Learning and Artificial Intelligence professionals who can help them implement these technologies and become technologically advanced.

As per the Machine Learning Market Research report, Machine Learning technology is predicted to grow over US$8.81 billion by the year 2022 with a compound annual growth rate (CAGR) of about 44.1 percent.

Source: Indeed

Without even noticing, we pass by several applications of Machine Learning on a daily basis. From this, we can gather that we are so consumed and used to this technology that it has become an essential and regular part of our day-to-day lives.

Over the years, Machine Learning has seen exponential growth. Hence, there is a high demand for Machine Learning professionals, in organizations across several industries, who have the ability and skills to implement Machine Learning in their systems and use it in the most profitable and effective manner. This technology has become extremely important and essential in enriching our lives, which is why organizations are filling their IT positions with professionals who have knowledge and experience in Machine Learning.

You must also check out this comprehensive Machine Learning Tutorial to know more!

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Machine Learning Engineer Salary

The job profile of a Machine Learning engineer is among the most highly paid IT employees and professionals.

Source: Indeed

Salary of a Machine Learning Engineer in the United States:

As per Glassdoor, the average income of a Machine Learning engineer in the United States is about US$114,000 p.a. This may increase to US$150,000 p.a.

Salary of Machine Learning Engineer in India

As per Glassdoor, in India, the average annual salary of a Machine Learning engineer is over ₹750,000, which may arise to ₹1,508,000.

Learn more about the salary structure of these professionals in our blog on Machine Learning Engineer Salary in India!

Top 10 Machine Learning Engineer Jobs

There are numerous job opportunities and career paths available for professionals in this domain. Leading organizations from all over the world are looking to hire Machine Learning engineers to get a step ahead in technology and business and stay competitive in the current digital market trends. Some of the highest-paid and most popular Machine Learning jobs are as follows:

  • Machine Learning engineer
  • Lead Machine Learning engineer
  • Data scientist
  • Research scientist
  • Artificial Intelligence engineer
  • Artificial Intelligence and Deep Learning researcher
  • Software engineer
  • Machine Learning scientist
  • Senior software engineer
  • Machine Learning expert
machine learning engineer jobs

Data Science IITM Pravartak

Machine Learning Engineer Job Description

There are numerous Machine Learning tasks performed by Machine Learning engineers. Some of the most significant tasks described in the Machine Learning job descriptions include:

  • Find, extract, and summarize important information
  • Make predictions on the basis of analyzed data
  • Calculate probabilities for certain outcomes
  • Autonomously adapt specific development methods
  • Optimize business tasks based on the gained patterns and insights

Here is a screenshot of a job posting for a Machine Learning engineer from Indeed in the United States.

To learn more about this technology, register for our Machine Learning Course and become proficient in this trending technology!

We will also assist you in creating a Machine Learning Engineer resume to give you a head start in your career.

Companies Hiring Machine Learning Engineers

Most companies have a lot of data that needs to be processed and examined on a regular basis. This process can be redundant, time-consuming, and extremely exhausting. It may require employees to repeat their working patterns, which can be frustrating and also be prone to errors due to exhaustion. This is why numerous leading companies are hiring Machine Learning engineers who can implement Machine Learning systems to help improve the companies’ business and save the time of their employees.

A few of these companies are:

  • Google
  • Amazon
  • Apple
  • Pinterest
  • McKinsey & Company
  • Deloitte

Future Scope of Machine Learning Engineers

Machine Learning will help you and your organization automate redundant and mundane tasks that do not necessarily require human efforts. The future scope of Machine Learning is on its way to a drastic change. This is why most organizations are implementing this technology and are looking to hire experts in this domain who can help them improve their business.

In this blog, you got in-depth knowledge about the various skills that you need to acquire to become a Machine Learning engineer. You also learned about the job roles and responsibilities of Machine Learning professionals and the job opportunities available in this domain.

If you have any doubts regarding this technology, then you can clear them on the Machine Learning Community!

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About the Author

Senior Research Analyst

As a Senior Research Analyst, Arya Karn brings expertise in crafting compelling technical content in Data Science and Machine Learning. With extensive knowledge in AI/ML, NLP, DBMS, and Generative AI, his works get lakhs of views across social platforms that benefit both technical and business spheres.