Why Machine Learning Developers Are in a High Demand?
Machine learning, including OpenCV development is becoming very popular. According to MarketsandMarket™ research report 2017, the market value of machine learning in the major industry verticals will reach $8.81 billion by 2022 at 44.1% compound annual growth rate (CAGR), from its existing market value of $1.03 billion in 2016. Before we deep dive into the machine learning market and the required human resources to cater the needs, let’s expand on technical aspects of machine learning.
Machine Learning Methods and Tools
Machine learning is a modern concept of learning based on artificial intelligence executed by intelligent computers or machines. Developing any application that helps machines to learn from the past data, examples and function/activity patterns without any explicit programming is known as machine learning.
According to Arthur Samuel one of the legendary machine learning thinkers, “the field of learning in which a computer or intelligent machine is provided with the capability of learning from the data without explicitly programming them”. So, it is very clear from the above definitions that machine learning is field of studies based on machine learning algorithms, where machines (not human) learn about how to understand the situation and respond appropriately. Different machine learning methods based on machine learning tools and techniques are adopted in this domain of studies.
A few very important machine learning methods are listed below.
- Reinforced machine learning algorithms
- Supervised machine learning algorithms
- Unsupervised machine learning algorithms
- Semi supervised machine learning algorithms
Machine learning engineers develop different kinds of machine learning tools that help machines learn through both with human intervention and without human intervention.
Popularity & Uses
Numerous industries and businesses are directly influenced by the effective and productive use of artificial intelligence based on the machine learning. According to the Forrester research report, the corporations and enterprises unleashing the power of customer insight CI into their insight-driven businesses are going to capture as much as $1.2 trillion revenue by 2020. The report further reveals that investment in artificial intelligence (AI) increased 300% in 2017 as compared to the investment made in 2016.
There are many domains of businesses, especially in telecommunication, healthcare, physical security, data prediction, information extraction and data analysis and others, where machine learning software is being extensively used. The major machine learning software applications include:
- Speech recognition application
- Image recognition application
- Statistical strategies regarding finance and trading
- Learning customer insights
- Business behavior predictions
- Customer behavior predictions
- Extraction of information from unstructured raw data
- Assessing output data based on multiple input variables by regression methodology
- And many others
Why to Use Machine Learning?
Every commercial, technical and social activity has transformed into a knowledge based activity in the present day information era. All business processes have become so complex owing to big volumes of valuable data and modern business approaches adopted in this competitive marketplace. The influence of real time data, business competitiveness, and modern technologies is substantially changing the landscapes of modern life.
To get insight into the human behavior, past data, future trends, and promising technologies, the power of normal human brain is not sufficient. It requires heavy processing power much more than a human mind can manage in a limited time frame. The analysis of big data coming from heterogeneous systems and business arena requires heavy power of machines to analyze in the complex business ecosystem.
Many kinds of data mining strategies are used by the machine learning specialists to analyze the complex and gigantic heterogeneous data to process the data into useful information at a fast pace and cheap cost. The major upsides of using machine learning into modern businesses include:
Languages a Machine Learning Developer Should Know
The machine learning specialists and programmers use numerous languages to develop machine learning algorithms, which are used to process and respond automatically without any explicit computer instructions through coding. The artificial intelligence programming uses numerous languages, platforms and tools for developing machine learning based applications.
According to the Towards Data Science research report, Python leads distantly from other popular languages with 57% popularity in the artificial intelligence developers. In this report, C/C++ stood distant second in the survey with 44% popularity in the domain of artificial intelligence programming.
The most important computer languages used in machine learning include:
- Python for general AI projects
- C/C++ for engineering projects
- R language
- Java for ERP solutions
- Artificial Intelligence Markup Language (AIML)
- Julia, Lisp & Scala
- Ruby & Matlab
According to IBM research, the demand of Python machine learning professionals was on the top of all other languages. So, the demand of Python artificial intelligence developers will last for many years to come.
Machine Learning Developers and Machine Learning Development Team
The computer programmers cum mathematicians who develop the machine learning applications and tools for the artificial intelligence purpose are known as machine learning developers. A programmer that creates logical algorithms based on logical reasoning and learning of the data is known as a machine learning developer. There is continuous growth in the demand of machine learning teams, especially the Python machine learning professionals.
Demand of Machine Learning Developers in the Market
According to IBM research cited in Forbes article, more than 700,000 jobs related data scientist are expected globally in 2017. The job demand will surge from 364,000 openings to whopping 2,720,000 openings by 2020 in the USA only. This huge demand in the machine learning developers will create new opportunities and rise in machine learning developer salary in the near future. The growth in other parts of the world, especially in Europe and Asia Pacific regions will increase tremendously in the upcoming years.
Demand of Machine Learning Engineers in Major AI Industries
Artificial intelligence is one of the most talked about technology in the present day marketplace. Many new startups are emerging in this domain along with the heavy investments of AI giant companies in this regards. According to a new technological article in Forbes, depicts a list of the companies that carry out huge research and development in the domain of artificial intelligence. The main companies that are the major drivers of the machine learning job market in artificial intelligence are listed below.
- IBM Corporation
- Google Inc
- Microsoft Corporation
- Pintrest Inc
- Apple Corporation
Above listed companies are only a few prominent companies that hire machine learning developers. There are many other companies dealing with data science also hire machine learning developers in a sizable number.
Main Skills of a Good Machine Learning Developer
The skills of a machine learning developer vary from industry to industry and the level of job. The fundamental activity of all machine learning teams is an artificial intelligence development in one way or the other. Let’s have a look at a generalized skill set required for a good machine learning developer.
- Knowledge of fundamental computer science concepts.
- Extensive knowledge of computer languages like Java, R, Python, C/C++ and others.
- Strong knowledge of mathematics, statistics and probability.
- Data evaluation and modeling such as, clustering, correlations and others.
- Great command over applying machine learning libraries and algorithms such as, H2O, Scikit-Learn, SparkMlib and others.
- Expert level knowledge of databases like SQL, Oracle, PostgreSQL and others.
- Knowledge of modern software engineering concepts and methodologies.
- Fluent in all major backend platforms like Linux, iOS, Windows, and others.
- Expert level knowledge of computer processing.
- Professional attitude like commitment, composition, target oriented and others.
Salary Comparison of Machine Learning Developers
According to IBM research report, the average salary for the job requiring machine learning skills is about $114,000. It is a bit higher than the advertised jobs, which is about $105,000 per annum. But, still the machine learning developer salary is in the high slabs in the industry.
Let’s compare the average salaries of a machine learning developer in 5 major countries.
These salaries may vary a bit with respect to location, city, experience, qualification and other factors.
Machine Learning Developer’s CV Samples
Normally, companies higher machine learning developers in three categories. The fundamental objective of hiring a machine learning engineer is to accomplish artificial intelligence development.
Let’s explore the main features of CVs for those three categories.
Entry Level Machine Learning Developer Resume Sample
Middle Level Machine Learning Developer CV Sample
Senior Level Machine Learning Developer Resume Example
Machine Learning Teams Working at Mobilunity
Right now our dedicated developers are working on exciting machine learning project of Canadian customer. He is involved in developing Social Patrol integrated machine learning capabilities, particularly image recognition component for social network streams pre-moderation and analysis. According to Sergey, Python developer working on this project:
“My project is about social network streams pre-moderation and analysis. We use supervised and unsupervised algorithms for Natural Language Processing and Image Classification”.
Why to Outstaff the Machine Learning Developers Hiring?
As we know, the machine learning engineer salary is very high in many parts of the world, especially in Europe and North America where major AI activities are concentrated at this time. The burden of stringent local rules and regulation governing the human resource hiring is also very high. So, it is always preferred option to outstaff the machine learning development projects to the third party contractors. It is very easy to manage and cheaper to finance an AI project through outstaffing.
There are many good outstaffing companies like Mobilunity that offer highly professional machine learning services at very cheap prices.