Hottest Jobs in Artificial Intelligence.

May 2, 2022

There are some things that sound astonishing but they are not, A similar case goes with fetching out the most prominent artificial intelligence job for yourself. While many industries remain severely affected by the consequences of the COVID-19 crisis, there is one sector that is actively recruiting: jobs in AI are booming, and the trend is showing no sign of slowing down. 

Artificial intelligence, and machine learning are changing the face of the global economy. How much do you know about the technology and its effects?

  • Just 15% of organizations use AI today; by next year, that number will be 31%.
  • A new type of artificial intelligence will become a bioelectronic hybrid. 
  • A new report carried out by a research agency in the UK said 110,500 jobs were posted in the past year. 
  • Every month for the past three years between 8000-10000 roles were posted online. 

Table Of Content

  • Exploring Artificial Intelligence Jobs market size.
  • Industries where Artificial Intelligence is being used intensively.
  • 7 most promising jobs in the Artificial Intelligence Industry.
  • How Artificial Intelligence will impact the job market in India?
  • Conclusion

Exploring Artificial Intelligence Jobs Market Size-

The artificial intelligence market is expanding, especially in light of the pandemic and the resulting business model adjustments. AI has been used by businesses all over the world to help with automation, workforce management, and digital transformation. 

The market for AI software reached $62.3 billion in 2020 and is predicted to rise at a breakneck pace to $997.8 billion by 2028.

Industries where artificial intelligence is being used intensively-, Apple Inc., Google LLC, Facebook, Microsoft, and International Business Machines Corporation are among the tech behemoths spending heavily on AI research and development. AI is being incorporated into nearly every instrument and program, from self-driving cars to life-saving medical equipment. 

AI has already been shown to be a major game-changer in the approaching digital world. These businesses are working on making AI more accessible for business applications. 

  • Healthcare
  • Banking & Financial Services
  • Retail & Ecommerce
  • Logistics & Transportation
  • Entertainment & Gaming
  • Manufacturing

7 most promising jobs in the Artificial Intelligence Industry-

These jobs are listed in descending order in accordance with the compensation paid in each role. 

1. Big Data Engineer/Architect

Big data architects are in charge of creating a framework that accurately mimics a company's big data requirements using data, hardware and software, cloud services, developers, and other IT infrastructure, to align an organization's IT assets with its business objectives. They are essential in any organization that uses big data solutions to work with massive data collections. 

They collaborate with banks, technology companies, information solutions companies, payment solutions, and consulting organizations, among other entities. 

Skills Required-

  • Knowledge of tools like Hive, Spark, HBase, Sqoop, Impala, Kafka, Flume, Oozie, MapReduce, etc. 
  • Spark Streaming, Spark, Kafka, and other Hadoop tools. 
  • Linux 
  • Python, Java, Shell Scripting, or Scala. 
  • SQL and Data modeling

2. Data Scientist 

In day-to-day operations, businesses are increasingly relying on data. A data scientist interprets raw data and pulls meaningful information from it. They then analyze the data to look for patterns and propose solutions that will help an organization grow and compete. If we had to define a data scientist, we'd say someone who extracts value from data.

Skills Required-

  • Python or R
  • SQL
  • SAS 
  • Tableau or PowerBI for Excel 
  • Deep Learning or Machine Learning
  • Apache Spark and Hadoop. 

3. User Experience

User experience (UX) designers are currently among the most in-demand creative talents. People who can help conceptualize and construct intuitive and engaging online experiences are needed across the country as businesses use AI more frequently to update their websites, and mobile apps, and to interact with customers in new ways.

Skills Required-

  • CSS and Figma 
  • Canva 
  • Javascript 
  • Miro Prototype Touchpoint Analysis 
  • Miro's User Experience Flow using Sitemaps

4. AI Engineer 

An Artificial Intelligence Engineer is a computer scientist whose goal is to create intelligent algorithms that can learn, analyze, and anticipate future occurrences. Their mission is to develop machines that can reason like a human brain. 

As a result, the AI engineer is also a researcher: he or she studies the human brain's functioning to create computer programs with human-like cognitive capacities.

Skills Required-

  • Java, Python, R, and C++.
  • Probability, Statistics, and Linear Algebra.
  • Cassandra, Hadoop, and MongoDB.
  • KNN, Support Vector Machine, linear regression, and Naive Bayes.
  • TensorFlow, Theano, PyTorch, and Caffe.

5. Natural Language Processing

By merging information, business process improvement, and technology, NLP engineers or developers are responsible for developing new solutions to meet business commitments and opportunities. 

The NLP Engineer's tasks include converting natural language input into relevant characteristics for classification algorithms utilizing NLP approaches.

Skills Required-

  • Text representation
  • Semantic extraction techniques 
  • Modeling
  • Python, Java, and R 
  • Frameworks - Keras or PyTorch 
  • Libraries - sci-kit
  • Products life cycle - Design, Development, Quality, Deployment, and Maintenance

6. Business Intelligence (BI) Developer

Business intelligence has evolved into a valuable asset for any modern company. The term "business intelligence" refers to a variety of strategies and technologies employed by businesses used to give actionable data to end-users so that they can make informed business decisions.

A business intelligence developer is an engineer who creates, delivers, and maintains business intelligence interfaces. Query tools, data visualization, interactive dashboards, ad hoc reporting, and data modeling tools are just a few examples.

Skills Required-

  • Data warehouse design - dimensional modeling.
  • Data mining.
  • Microsoft Power BI, Tableau, or Oracle BI.
  • Python or R.
  • SQL, SQL Server Integration Services (SSIS), and SQL Server Reporting Services (SSRS).

7. Data Analytics

To answer a query or solve an issue, a data analyst collects, cleans, and evaluates data sets. 

Business, finance, criminal justice, science, medical, and government are just a few of the fields where data analysts operate. 

What types of clients should a business focus on in its next marketing campaign? 

What age group is the most susceptible to disease? What behavioral patterns are linked to financial fraud?

Skills Required-

  • Google Sheets and Microsoft Excel 
  • SQL 
  • R or Python 
  • Tableau or  Microsoft Power BI 
  • Jupyter Notebooks 
  • SAS

You can check the salaries for AI sector here-

How Artificial Intelligence will impact the job market in India?

“PM Modi has a goal of making India a global center for artificial intelligence. Many Indians are working on technology all across the world, and many more will in the future” . He spoke about building a conducive learning environment at the RAISE Summit, citing initiatives such as the National Educational Technology Forum (NETF).

According to The Indian Express, “Artificial Intelligence would create nearly 20 million employment by 2025. These figures reflect the positive response and the most recent technological advancements in every industry imaginable” 

Disease detection, mental health counseling, weather forecasting, crop predictions, studies, designing, urban city planning, sewage systems, traffic planning, disaster management, and fashion and space research are only a few of the fields that have been explored. It's all been touched by AI.


There has been much information and research on the impact of AI on work, ranging from nature of jobs, to workplace configurations to issues around bias, privacy, ethics and more, challenging many assumptions that we have lived with in the past and creating new possibilities. The more we understand the nature of unique data sets, the better placed we will 

be to make best use of the benefits and mitigate the risks that these technologies bring to us.

So, looking for a career change/start? Grab the opportunity today.

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June 29, 2022

Project Management for AI-ML-DL Projects

Managing a project properly is one of the factors behind its completion and subsequent success. The same can be said for any artificial intelligence (AI)/machine learning (ML)/deep learning (DL) project. Moreover, efficient management in this segment holds even more prominence as it requires continuous testing before delivering the final product.

An efficient project manager will ensure that there is ample time from the concept to the final product so that a client’s requirements are met without any delays and issues.

How is Project Management Done For AI, ML or DL Projects?

As already established, efficient project management is of great importance in AI/ML/DL projects. So, if you are planning to move into this field as a professional, here are some tips –

  • Identifying the problem-

The first step toward managing an AI project is the identification of the problem. What are we trying to solve or what outcome do we desire? AI is a means to receive the outcome that we desire. Multiple solutions are chosen on which AI solutions are built.

  • Testing whether the solution matches the problem-

After the problem has been identified, then testing the solution is done. We try to find out whether we have chosen the right solution for the problem. At this stage, we can ideally understand how to begin with an artificial intelligence or machine learning or deep learning project. We also need to understand whether customers will pay for this solution to the problem.

AI and ML engineers test this problem-solution fit through various techniques such as the traditional lean approach or the product design sprint. These techniques help us by analysing the solution within the deadline easily.

  • Preparing the data and managing it-

If you have a stable customer base for your AI, ML or DL solutions, then begin the project by collecting data and managing it. We begin by segregating the available data into unstructured and structured forms. It is easy to do the division of data in small and medium companies. It is because the amount of data is less. However, other players who own big businesses have large amounts of data to work on. Data engineers use all the tools and techniques to organise and clean up the data.

  • Choosing the algorithm for the problem-

To keep the blog simple, we will try not to mention the technical side of AI algorithms in the content here. There are different types of algorithms which depend on the type of machine learning technique we employ. If it is the supervised learning model, then the classification helps us in labelling the project and the regression helps us predict the quantity. A data engineer can choose from any of the popular algorithms like the Naïve Bayes classification or the random forest algorithm. If the unsupervised learning model is used, then clustering algorithms are used.

  • Training the algorithm-

For training algorithms, one needs to use various AI techniques, which are done through software developed by programmers. While most of the job is done in Python, nowadays, JavaScript, Java, C++ and Julia are also used. So, a developmental team is set up at this stage. These developers make a minimum threshold that is able to generate the necessary statistics to train the algorithm.  

  • Deployment of the project-

After the project is completed, then we come to its deployment. It can either be deployed on a local server or the Cloud. So, data engineers see if the local GPU or the Cloud GPU are in order. And, then they deploy the code along with the required dashboard to view the analytics.

Final Words-

To sum it up, this is a generic overview of how a project management system should work for AI/ML/DL projects. However, a point to keep in mind here is that this is not a universal process. The particulars will alter according to a specific project. 

Reference Links:,product%20on%20the%20right%20platform.

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June 29, 2022

Top 7 AI & ML start-ups in Telecom Industry in India

With the multiple technological advancements witnessed by India as a country in the last few years, deep learning, machine learning and artificial intelligence have come across as futuristic technologies that will lead to the improved management of data hungry workloads.


The availability of artificial intelligence and machine learning in almost all industries today, including the telecom industry in India, has helped change the way of operational management for many existing businesses and startups that are the exclusive service providers in India.


In addition to that, the awareness and popularity of cloud GPU servers or other GPU cloud computing mediums have encouraged AI and ML startups in the telecom industry in India to take up their efficiency a notch higher by combining these technologies with cloud computing GPU. Let us look into the 7 AI and ML startups in the telecom industry in India 2022 below.


Top AI and ML Startups in Telecom Industry 

With 5G being the top priority for the majority of companies in the telecom industry in India, the importance of providing network affordability for everyone around the country has become the sole mission. Technologies like artificial intelligence and machine learning are the key digital transformation techniques that can change the way networks rotates in the country. The top startups include the following:


Founded in 2021, Wiom is a telecom startup using various technologies like deep learning and artificial intelligence to create a blockchain-based working model for internet delivery. It is an affordable scalable model that might incorporate GPU cloud servers in the future when data flow increases. 


As one of the companies that are strongly driven by data and unique state-of-the-art solutions for revenue generation and cost optimization, TechVantage is a startup in the telecom industry that betters the user experiences for leading telecom heroes with improved media generation and reach, using GPU cloud online


As one of the strongest performers is the customer analytics solutions, Manthan is a supporting startup in India in the telecom industry. It is an almost business assistant that can help with leveraging deep analytics for improved efficiency. For denser database management, NVIDIA A100 80 GB is one of their top choices. 


Just as NVIDIA is known as a top GPU cloud provider, NetraDyne can be named as a telecom startup, even if not directly. It aims to use artificial intelligence and machine learning to increase road safety which is also a key concern for the telecom providers, for their field team. It assists with fleet management. 

KeyPoint Tech

This AI- and ML-driven startup is all set to combine various technologies to provide improved technology solutions for all devices and platforms. At present, they do not use any available cloud GPU servers but expect to experiment with GPU cloud computing in the future when data inflow increases.



Actively known to resolve customer communication, it is also considered to be a startup in the telecom industry as it facilitates better communication among customers for increased engagement and satisfaction. 


An AI startup in Chennai, Facilio is a facility operation and maintenance solution that aims to improve the machine efficiency needed for network tower management, buildings, machines, etc.


In conclusion, the telecom industry in India is actively looking to improve the services provided to customers to ensure maximum customer satisfaction. From top-class networking solutions to better management of increasing databases using GPU cloud or other GPU online services to manage data hungry workloads efficiently, AI and MI-enabled solutions have taken the telecom industry by storm. Moreover, with the introduction of artificial intelligence and machine learning in this industry, the scope of innovation and improvement is higher than ever before.




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June 29, 2022

Top 7 AI Startups in Education Industry

The evolution of the global education system is an interesting thing to watch. The way this whole sector has transformed in the past decade can make a great case study on how modern technology like artificial intelligence (AI) makes a tangible difference in human life. 

In this evolution, edtech startups have played a pivotal role. And, in this write-up, you will get a chance to learn about some of them. So, read on to explore more.

Top AI Startups in the Education Industry-

Following is a list of education startups that are making a difference in the way this sector is transforming –

  1. Miko

Miko started its operations in 2015 in Mumbai, Maharashtra. Miko has made a companion for children. This companion is a bot which is powered by AI technology. The bot is able to perform an array of functions like talking, responding, educating, providing entertainment, and also understanding a child’s requirements. Additionally, the bot can answer what the child asks. It can also carry out a guided discussion for clarifying any topic to the child. Miko bots are integrated with a companion app which allows parents to control them through their Android and iOS devices. 

  1. iNurture

iNurture was founded in 2005 in Bengaluru, Karnataka. It provides universities assistance with job-oriented UG and PG courses. It offers courses in IT, innovation, marketing leadership, business analytics, financial services, design and new media, and design. One of its popular products is KRACKiN. It is an AI-powered platform which engages students and provides employment with career guidance. 

  1. Verzeo

Verzeo started its operations in 2018 in Bengaluru, Karnataka. It is a platform based on AI and ML. It provides academic programmes involving multi-disciplinary learning that can later culminate in getting an internship. These programmes are in subjects like artificial intelligence, machine learning, digital marketing and robotics.

  1. EnglishEdge 

EnglishEdge was founded in Noida in 2012. EnglishEdge provides courses driven by AI for getting skilled in English. There are several programmes to polish your English skills through courses provided online like professional edge, conversation edge, grammar edge and professional edge. There is also a portable lab for schools using smart classes for teaching the language. 

  1. CollPoll

CollPoll was founded in 2013 in Bengaluru, Karnataka. The platform is mobile- and web-based. CollPoll helps in managing educational institutions. It helps in the management of admission, curriculum, timetable, placement, fees and other features. College or university administrators, faculty and students can share opinions, ideas and information on a central server from their Android and iOS phones.

  1. Thinkster

Thinkster was founded in 2010 in Bengaluru, Karnataka. Thinkster is a program for learning mathematics and it is based on AI. The program is specifically focused on teaching mathematics to K-12 students. Students get a personalised experience as classes are conducted in a one-on-one session with the tutors of mathematics. Teachers can give scores for daily worksheets along with personalised comments for the improvement of students. The platform uses AI to analyse students’ performance. You can access the app through Android and iOS devices.

  1. ByteLearn 

ByteLearn was founded in Noida in 2020. ByteLean is an assistant driven by artificial intelligence which helps mathematics teachers and other coaches to tutor students on its platform. It provides students attention in one-on-one sessions. ByteLearn also helps students with personalised practice sessions.

Key Highlights

  • High demand for AI-powered personalised education, adaptive learning and task automation is steering the market.
  • Several AI segments such as speech and image recognition, machine learning algorithms and natural language processing can radically enhance the learning system with automatic performance assessment, 24x7 tutoring and support and personalised lessons.
  • As per the market reports of P&S Intelligence, the worldwide AI in the education industry has a valuation of $1.1 billion as of 2019.
  • In 2030, it is projected to attain $25.7 billion, indicating a 32.9% CAGR from 2020 to 2030.

Bottom Line

Rising reliability on smart devices, huge spending on AI technologies and edtech and highly developed learning infrastructure are the primary contributors to the growth education sector has witnessed recently. Notably, artificial intelligence in the education sector will expand drastically. However, certain unmapped areas require innovations.

With experienced well-coordinated teams and engaging ideas, AI education startups can achieve great success.

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