5 compelling reasons to switch to ML career

5 Reasons to Switch to a Machine Learning Career in 2024

Last updated by Rishabh Dev Choudhary on Aug 30, 2024 at 08:18 PM | Reading time: 8 minutes

Why Demand for Machine Learning is Growing?

Once confined to the work area of data science and data analytics, machine learning is now being utilized across many industries including healthcare, tech, manufacturing, and finance. With every passing day, an increasing number of companies are investing in machine learning to enhance efficiency, reduce costs, and gain competitive advantage.

As AI technologies continue to evolve, the demand for machine learning experts who can leverage these technologies to develop innovative solutions is growing at a rapid pace.

5 Reasons to Switch to Machine Learning

Let’s look at a few compelling reasons to switch to a machine learning career.

ML Enhances Career Prospects

According to many recent reports, the machine learning (ML) market is expected to grow at an annual CAGR of 38.8% between 2024 and 2029 The market’s value is expected to increase multiple times from $21.1 in 2021 to $209.91 billion by 2029.

These statistics convey that machine learning will occupy a decent market share in the coming years. Its reach will spread to almost every industrial sector, and create many job opportunities for ML specialists in the coming years.

If you aspire to be a part of one of the most lucrative IT professions, switch to the machine learning career.

ML Brings Lucrative Salaries

With exciting career prospects, come even more lucrative salaries. Typically, a machine learning expert draws a base salary between $70,000 to $250,000.

Whereas an entry-level machine learning engineer’s base salary is in the range of $78,500 to $118,000, a machine learning vice president’s base salary is in the range of $158,600 to $210,000. A CEOmachine learning draws a higher pay package.

However, these pay packages vary depending on the industry an ML expert serves. Sectors with decent cash flows like IT, medicare, and finance offer better pay packages than other sectors.

With the ever-increasing demand for machine learning experts, the salaries of ML engineers are expected to rise even higher in the coming years.

Source of Salary Related Information: Glassdoor, ZipRecruiter

Also Read: Machine Learning Engineer Salary in United States

ML Boosts Knowledge and Proficiency

At present, machine learning is probably one of the most in-demand professions in IT. A career in machine learning is full of opportunities, yet is intellectually challenging as well.

Mustering the skills required to succeed as an ML expert broadens your knowledge and expertise. And once you apply this expertise to improve business operations through automation and cost control, it can make you a valuable asset to any company.

For instance, by using machine learning algorithms you can analyze vast amounts of data very quickly to gather valuable insights that may benefit your organization in enhanced decision-making.

Humans produce approximately 2.5 quintillion bytes of data every day. Fortunately, we have the machine learning technology in place to not only ingest such a huge amount of data but also provide insights that benefit individuals, organizations, and the world.

You can also help your company automate mundane and repetitive tasks that are time-consuming. This will help your resources to focus on more creative tasks.

Also read: How difficult is it to be a machine learning engineer/scientist?

ML Provides Better Understanding of Customer Behavior

From providing movie recommendations and shopping suggestions based on your past purchase experiences to making chatbots generate human-like responses to customer queries, machine learning technology does a lot of things.

With this technology at the helm, each client’s unique requirements, preferences, and problem areas can be understood. Each customer is then provided with tailor-made products and services, compelling offers, and eye-catching discounts. By doing so, the companies can maintain long-term relationships with content customers.

Don’t you think this is exactly what every company wants as an ideal return on investment?

So, understanding customer behavior is another compelling reason to switch to machine learning.

Also read: Everything You Need to Know about Clustering and Segmentation in Customer Profiling

ML is Considered the Skill of the Century

Machine learning is set to replace lots of human jobs in the future and will create lots of new ones. It’s fair to say that machine learning is the skill of the century that everyone should understand, at least to some extent.

Since machine learning is changing the face of industries across the world, it’s exciting to be a part of this revolution. You may start with self-learning or pursue a comprehensive machine learning course to get the required knowledge.

After acquiring the required skills, you can start applying for appropriate machine learning positions. Here are a few toughest machine learning questions to help you prepare for tech-intensive interviews.

Typical Career Path for a Machine Learning Expert

Machine Learning Engineer: Career path of a machine learning expert starts with the machine learning engineer position. Machine learning engineers develop applications that automate repetitive tasks previously handled by humans. Once trained, machines handle these tasks efficiently, with minimal errors.
Senior Machine Learning Engineer: After promotion, an ML expert acquires the position of senior machine learning engineer. In this role, the ML expert designs and builds production-grade AI solutions, which use machine learning models.

Senior ML Engineers provide ML expertise in all the projects of the company and work closely with data scientists, ML engineers, AI service designers, and chief ML officers.

Head Machine Learning Engineer: Head ML Engineers lead a team of machine learning engineers and oversee the planning, execution, and delivery of machine learning projects. Machine Learning Engineers also mentor, guide, and motivate the teams to ensure that the teams work efficiently.
VP/CEO Machine Learning: VP/CEO Machine Learning oversees the company’s machine learning projects from a strategic standpoint, often aligning these strategies with the company’s vision and objectives. Their expertise extends beyond the technical side of ML projects and encompasses their business and organizational aspects as well.

Transition Your Career to AI/ML With Interview Kickstart!

If you wish to pursue a lucrative and in-demand career in AI/ML, you can consider enrolling in the machine learning course offered by Interview Kickstart.

The ed-tech company has collaborated with FAANG instructors who personally teach the latest machine learning skills to aspiring candidates.

Along with ML, Interview Kickstart also offers a specialized course in data science that covers concepts including classical and advanced machine learning, deep learning, big data analysis, and data visualization, to name a few.

Those interested in Generative AI can pursue an Applied Gen AI course to get a comprehensive understanding of various Gen AI concepts.

You can also read the success stories of professionals who, after completing our courses, have acquired high-paying jobs in the AI/ML domain.

FAQs: Five Reasons To Switch to Machine Learning

1. What Is Exciting About Machine Learning?

What is exciting about machine learning is the fact that you can create something unique on your own and make it work. What should fascinate ML enthusiasts is the probable reality that one day machines will be so advanced that they will work alongside humans in their day-to-day work.

2. What Are The 4 Basics of Machine Learning?

There are four basic types of machine learning: supervised learning, unsupervised learning, semi supervised learning, and reinforcement learning. It will depend on the machine learning engineer to select any of the four machine learning algorithms.

3. How Do I Switch My Career to Machine Learning?

To make a career switch to machine learning one needs to follow a structured approach and a year of consistent and focused study, either through self-learning or through a comprehensive machine learning course.

Subsequently, aspirants can opt for live projects through boot camps or through various freelance sites where such projects are available to opt for. Here are career tips to make your ML transition smoother.

4. Can We Learn ML Without Coding?

Yes. ML career aspirants can learn machine learning without coding. In the no-code machine learning approach, one uses point-and-click interfaces to build models that do not require coding. With this approach, one can build efficient machine learning models with a quicker turnaround time than the code-based approach.

Related Articles:

AUTHOR

Rishabh Dev Choudhary

No items found.

Register for our webinar

How to Nail your next Technical Interview

Step 1

Step 2

Congratulations!

You have registered for our webinar

Oops! Something went wrong while submitting the form.

Step 1

Step 2

Confirmed

You are scheduled with Interview Kickstart.

Redirecting...

Oops! Something went wrong while submitting the form.

Worried About Failing Tech Interviews?

Attend our webinar on
"How to nail your next tech interview" and learn

Hosted By

Ryan Valles

Founder, Interview Kickstart

Our tried & tested strategy for cracking interviews

How FAANG hiring process works

The 4 areas you must prepare for

How you can accelerate your learnings

Register for Webinar

How to Nail your next Technical Interview

Nick Camilleri

5 Reasons to Switch to a Machine Learning Career in 2024

Contents

Rishabh Dev Choudhary

Attend our Free Webinar on How to Nail Your Next Technical Interview

How to Nail your next Technical Interview

Worried About Failing Tech Interviews?

Tools to Enhance Full Stack Development with AI

The Future of Data Science: Emerging Trends and Opportunities

Data-Driven Decision Making: Your Roadmap to Business Success

The Business Impact of Machine Learning: Real-world Case Studies

What is OpenAI? Everything You Need to Know

Mock Interviews for Generative AI: Essential Practice to Land Top AI Roles

Top Python Scripting Interview Questions and Answers You Should Practice

Complex SQL Interview Questions for Interview Preparation

Zoox Software Engineer Interview Questions to Crack Your Tech Interview

Rubrik Interview Questions for Software Engineers

Top Advanced SQL Interview Questions and Answers

Twilio Interview Questions

Ready to
Enroll?

Next webinar starts in

How to Nail your next Technical Interview

You may be missing out on a 66.5% salary hike*

Nick Camilleri

How many years of coding experience do you have?

FREE course on 'Sorting Algorithms' by Omkar Deshpande (Stanford PhD, Head of Curriculum, IK)

How can we help?

Register for Webinar

Read our Reviews

Send us a note

5 Reasons to Switch to a Machine Learning Career in 2024

Contents

Rishabh Dev Choudhary

Attend our Free Webinar on How to Nail Your Next Technical Interview

How to Nail your next Technical Interview

Worried About Failing Tech Interviews?

Tools to Enhance Full Stack Development with AI

The Future of Data Science: Emerging Trends and Opportunities

Data-Driven Decision Making: Your Roadmap to Business Success

The Business Impact of Machine Learning: Real-world Case Studies

What is OpenAI? Everything You Need to Know

Mock Interviews for Generative AI: Essential Practice to Land Top AI Roles

Top Python Scripting Interview Questions and Answers You Should Practice

Complex SQL Interview Questions for Interview Preparation

Zoox Software Engineer Interview Questions to Crack Your Tech Interview

Rubrik Interview Questions for Software Engineers

Top Advanced SQL Interview Questions and Answers

Twilio Interview Questions

Ready to Enroll?

Next webinar starts in

Ready to
Enroll?