Career in Machine Learning: Popularity, Why Should You Pursue, Required Skills

It is expected that AI will create a business value of around $4 billion by the end of 2022. Over one-third of companies in India have either already started spending on data science and machine learning or are planning to do it in the coming time.

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If we specifically talk about job prospects for machine learning engineers, there was an increase more than 330% in job postings for this position worldwide in the period spanning 2015-2018. The average base salary of a machine learning engineer in India is around Rs 700000 per annum, more than almost every other job role. No wonder jobs in AI and machine learning are considered “the hottest jobs of the century.” Let us take a deeper plunge then and learn more about what you can expect from a career in machine learning. 

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Career options in Machine Learning

• Machine learning engineer: A machine learning engineer is a professional who trains machines to make future predictions. Knowledge of Java, Python, Scala, data modelling, programming, probability, machine learning algorithms, statistics, and system design is very important to become a machine learning engineer. 

Machine learning engineer utilises their skills to automate tasks where the machine can perform them without human intervention. The engineers also develop programs and code to extract information from large chunks of data.

Machine learning is expected to grow rapidly, and the market is multiplying for machine learning. The market for machine learning is expected to reach USD 209.91 billion by 2029 (Source).

The average machine learning engineer salary is 7.5 lakhs per annum. The average salary ranges from 3.5 lakhs per annum to 22.0 lakhs per annum (Source).

• BI developer: The role of a BI developer is to use ML and data analytics techniques to work on large amounts of data and make it useful for the decision-makers of a business. A BI developer needs to be proficient in Power BI, Perl, SQL, Python, SQL, and databases.

A BI developer is responsible for maintaining, developing and designing a BI model. They are also responsible for maintaining and checking up on health or monitoring the security, cloud infrastructure, and more.

The market for business intelligence is increasing. The demand for BI is projected to grow at a  CAGR of 8.7% (Source).

The average salary of a BI developer is 5.9 lakhs per annum. The average salary ranges from 3.6 lakhs per annum to 11.0 lakhs per annum (Source). A career in machine learning is a lucrative option; one should invest efforts in learning the skills required and develop a robust portfolio of themselves to gain better job opportunities in the future. 

• Data scientist: The role of a data scientist is somewhat similar to that of a BI developer. A data scientist also has to work on large datasets to help a business’s decision-makers make better decisions backed by data. A data scientist must be proficient in predictive modelling, machine learning, statistical research, big data, data mining, and programming languages. 

The market for data science is enormous, as data is the centre of almost every industry today. Organisations require professionals who can work with data effortlessly, which helps extract to provide meaningful information. There are various roles in the data science industry; to procure a good role for oneself, one must invest efforts into developing skill sets and a solid profile.

The market is multiplying, and the market size is expanding. It is expected to reach  USD 378.7 billion by 2030 (Source).

The average salary of a data scientist is 10.5 lakhs per annum. The average salary ranges from 4.5 lakhs per annum to 26.0 lakhs per annum (Source).

• Human-centred machine learning designer: This professional works on machine learning algorithms that are designed for humans and their choices. So if you use Netflix and other such services, you would know how it suggests you different movies and series based on what you have watched before. So a human-centred machine learning designer uses pattern recognition and information processing techniques to develop systems that can help in creating more brilliant experiences based on human preferences in different situations. 
• Natural language processing or NLP scientist: An NLP scientist develops or trains machines in a way that they learn to understand different languages that human beings use. In other words, you can say that NLP scientist trains machines to interact with humans. So an NLP scientist needs to know how machine learning works. Also, this professional should be excellent in at least one language humans speak. 

The global market for NLP is expanding rapidly, and the market is expected to reach USD 127.26 billion in 2028 (Source). 

There are vast applications of NLP models in today’s time. Technology has advanced, and the products of NLP have crept into the market. 

Some real-life applications for NLP are email-filter, predictive texts, chatbot analysis, language translation and more. There are numerous jobs available in machine learning jobs for freshers and experienced professionals. 

One must possess skill sets and understand the industry requirements to gain better job opportunities at work. 

The average salary of a Natural Language Processing Engineer is 8.8 lakhs per annum. The average salary ranges from 3.5 lakhs per annum to 25.5 lakhs per annum (Source).

Why are Machine Learning Roles so popular?

There has been a symbolic explosion in the usage of machine learning. You will see smart learning algorithms everywhere – from marketing campaigns and emails to mobile applications and more. Indicating that a career in machine learning is, at the moment, one of the most in-demand careers across the world. So if working with smart machines interests you, this is the perfect career option for you. You should start acquiring skills to make the most of the machine learning career opportunities on offer.

But have you ever thought about why has machine learning become such a popular skill in such a short span of time? It is because most of companies in India and throughout the world are incorporating artificial intelligence and machine learning into their existing systems to make them smarter and more efficient.

Machine learning has enabled organizations to automate their tasks, which has led to less human intervention, more accurate responses and better decision-making. 

Machines have increased the efficiency of functions and have lessened the time taken to perform tasks. Organizations can efficiently utilize their resources and arrive at decisions by working through data. The decision-making process has become more accurate with the inclusion of data.

So as there is a race amongst companies to adopt machine learning, to grow faster, the need to hire more people skilled in machine learning has also gone up a few notches. Companies are willingly spending large sums of money in this ML adoption that includes the hiring of experts because they know what’s at stake here and how this investment can bring huge returns. Machine learning experts can make this a seamless transition and ensure more result-oriented business decision making going into the future. 

The machine learning experts bring their skill sets to the organization. Thus making the company more technologically advanced. They can work swiftly with the data and make machines learn from it. Because of their skills and intelligence in machine learning jobs salary is high. Moreover, career advancement is also huge. 

In an article published in Forbes, it was mentioned that patents in machine learning increased at a rate of 34% CAGR between 2013 and 2017. And do you companies which companies most of these patents belong to? The likes of Facebook, Intel, IBM, LinkedIn, and Microsoft are at the top in this running. These companies have realized that machine learning and AI are the technologies that will help them do well in the future.

Other companies have followed suit. We have more companies that use machine learning applications now, which is one of the biggest reasons behind its popularity, as well as the high demand for jobs in this field. The right time to pursue a career in machine learning is now. If you are looking for more reasons, read on!

Why should you pursue a career in machine learning? 

Machine learning and AI is the ammunition that powers machine and bots. Machine learning gives businesses the ability to build programs that can modify and update machines and make them seamlessly adapt to different environments – to get things done right and faster.

Businesses need machine learning professionals who can power them into the lead, beyond all their competitors, when it comes to ML adoption. Here are a few more reasons to help you decide in favour of pursuing a career in machine learning:

1. The future is artificial intelligence and machine learning. Our discussion, until now, has quite unequivocally suggested that ML is the skill of the future and that your job prospects with this skill will never die down, not at least in the next decade or two. And we have also shared stats that clearly say that there is a dearth of skilled ML professionals to fill thousands of open ML positions. So what you need to do right now is gain expertise in the field. Once you do that, you can begin a career that is both high paying and secure. 

2. The field is ideal for people who are interested in working on real challenges. Businesses, in the modern era, face a lot of challenges that machine learning can help them overcome. So after acquiring the required skills, if you choose to become an ML engineer, one of the many career options available at your disposal, you will be working on real challenges with significant consequences. You will build solutions that affect both individuals and businesses on some level. If you are looking for a job that gives you high satisfaction, not too many other jobs can beat an ML job in that respect. 

3. Exponential career growth. Everything said we should accept that machine learning is still in its early stage of adoption. However, the future seems very bright. So people who are willing to enter this field would have no qualms about making this decision later in their lives. The average salary in machine learning makes it a lucrative career option for everyone out there.

Since there is still a long way for this industry to reach its peak, the salary that you make as an ML professional will continue growing with every year. All you need to do is keep upskilling and updating yourself. As ML advances and matures, you will have the opportunity to experience exponential growth in your career and land a dream job with your ideal company.

4. Option to move to data science. Professionals skilled in machine learning have so many avenues open to them when it comes to their respective careers. With the right set of skills, you can even don the hat of a data scientist, which is again a very lucrative career opportunity. You can gain skills that make you a relevant resource for both these positions. Once you do so, you will be a part of a journey that is exciting, rewarding, and filled with knowledge, challenges, and opportunities. 

Machine Learning Skills

Now that you know why you should choose a career in machine learning and have perhaps made a decision as well, let us tell you a few important skills that you need to have to make the most of this opportunity.

• Statistics and probability: Your understanding of algorithms has a lot to do with your knowledge of theories. Hidden Markov models, Naïve Bayes, and Gaussian Mixture, amongst other models, are great examples. If you aren’t good at statistics and probability, you will find these algorithms very difficult to understand. 

Statistics is an important aspect of machine learning algorithms. This allows for better analyses and interpretation of data. The professionals can understand the patterns that are not apparent. This helps the professionals to draw inferences and new conclusions from the data sets.

• Data evaluation and modeling: An important part of ensuring the efficiency of the estimation process with ML is to evaluate the effectiveness of different models at regular intervals. You can use different methods, such as regression and classification, to measure the error or accuracy of a given model. You also need an evaluation strategy to go with it. 

The accurate modelling and evaluation of the data results in better-crafted models. The machines can be better automated, which can help in an effective decision-making process. 

Data modelling facilitates the creation of data that is simplified, logical and free from errors. Data modelling also helps in producing content that is of high quality and is structured. 

• ML algorithms: Knowing how different machine learning algorithms work and which algorithm fits in a particular situation is very important. You would need to develop an understanding of subjects like partial differential equations, gradient descent, quadratic programming, convex optimization, and others. 

The knowledge of ML algorithms helps professionals in performing their functions in a much easier way. The ML algorithms support professionals in developing robust ML models. 

Moreover, the ML algorithms also facilitate a better understanding of customer trends, behavior and analysis. The software can predict accurate information, thus increasing the quality of the final product.

• Programming languages: For a career in machine learning, you also need to be skilled in different programming languages, such as Java, R, Python, and C++. These languages will help you at different stages of your machine learning project. 
• Signal processing techniques: Feature extraction is very important to machine learning. You may have to work with several advanced signal processing algorithms, including bandlets, shearlets, contourlets, and curvelets, amongst others. Learn more about machine learning required skillsets.

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Conclusion

A career in machine learning helps you run alongside the digital revolution that we all know is currently happening in almost every sector. Professionals skilled in machine learning have several avenues open to them, from which they can choose the one that interests them the most and pays them according to their skills.

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