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Choose the Right Machine Learning Path..

Once you have gained the required Machine Learning skills, there are five top career choices that you can go for -

  1. Machine Learning Engineer - Choosing this path will require you to be mainly involved in designing and developing Machine Learning Systems and apps by utilizing Machine Learning Algorithms and tools. It will be your job to build and develop self-sufficient Machine Learning applications by statistically analyzing and make them flawless with the help of test results. Conducting various Machine Learning experiments by coding in Python, C++, Scala , Java and R etc. is also required.

  2. Data Scientist - Harvard Business has named the job profile of a Data Scientist as the 'Sexiest Job of the 21st Century'. If popularity of this job is not understood by this article then what will ? Data Scientist are top class professionals whose expertise is to make the best use of technologies like Big Data, Deep Learning, AI , ML and analytical tools on a timely basis to source, pile up, execute , analyze and simplify large quantities of data. Their top responsibility is to retrieve important information from massive datasets that can be converted into something of great economic asset.

  3. NLP Scientist - Natural Language processing (NLP) is a process whose target is to enable machine to comprehend natural human languages. A professional with the right ML skills and also fluent in syntax, grammar and spelling of at minimum one language can be a good NLP Scientist. With these skills, they'll be responsible for design and development of machines and apps the can understand , interpret the various modes of a human language and also translate it in to other languages, also in spoken words. The idea here is let machines respond and act to human languages as easily as humans do.

  4. Software Developer/Engineer (AI/ML) - Software Developers with specialization in Machine Learning/Data Analytics/ Artificial Engineering are the great minds behind smart machines. Their main job is to develop efficient ML algorithms and applications. Software Developers/Engineers design, develop, and install AI/ML software solutions; create specific computer functions; prepare product documentation, flowcharts, layouts, diagrams, charts, etc. for visualization; write and test code; create technical specifications, upgrade and maintain systems, and much more.

  5. Human-Centered Machine Learning Designer - Machine Learning has a separate field that is dedicated to designing Machine Learning algorithms focussed around humans. Hence, the name Human-Centered Machine Learning. Human-Centered Machine Learning Designers are responsible for design and development of smart systems that can adapt to the preferences and behavior patterns of individual humans by learning through information processing and pattern recognition. These systems require minimal or no human intervention or even cumbersome programs to account for every conceivable user scenarios. Few television giants like Amazon and Netflix's user Recommendation Engine is an excellent example of Human-Centered Machine Learning

Conclusion - While these are the top five Machine Learning career paths, there are many other career pathways in this domain, such as Data Analyst, Data Architect, Cloud Architect, and Business Intelligence Developer, to name a few. Ultimately the choice of a Machine Learning career path depends on you – what do you wish to specialize in and what skills you have and wish to acquire. To know about the right skills to become a ML Engineer, Read This

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