Artificial Intelligence or AI seems to be the buzzword for any and every business in today’s world. AI is the tech of the future available today. This has driven multiple projects across industries in the field of Artificial Intelligence. Businesses across industries have come up with path-breaking applications using AI. While it is true that AI has helped reduce the workforce, it has also increased the demand in niche jobs in and around the Artificial Intelligence domain.
Artificial Intelligence jobs appear to be more fulfilling and rewarding than other jobs in today’s market. Businesses require a talent pool with a wide range of skills to come out with an AI-enabled product. In this write up we shall dip into role of artificial intelligence, the various artificial intelligence jobs available in the market, and artificial intelligence career paths. We shall also take a sneak peek at future artificial intelligence jobs.
In this article let us look at:
With the increase in AI adoption, there is an obvious increase in artificial intelligence jobs. You can tap into this demand if you have a data-driven mind and a strong penchant for transforming existing systems into an AI-based or AI-driven one. The demand for AI-related talent is an ever-increasing one and does not show any signs of ebbing. AI around the world is mostly a research topic with a small part of AI helping us achieve what we have already like driverless mobility.
There is so much more that AI can offer and is still said to be only in its nascent stage. As far as artificial intelligence jobs in India, specifically in the industries which run on economies of scale are much in demand. Let’s take a quick look at a few popular roles in the AI space.
An AI engineer or Machine Learning Engineer/ Developer is a role which engineers in other words designs and develops the AI system/model in its entirety or in parts. Such a role requires the resource to possess proven skills in Statistical Analysis, Statistical Tests, Design and development of Machine Learning algorithms, develop Deep Learning systems, strong software engineering and programming skills based on a solid computer science foundation. The AI Engineer is entrusted with the artificial intelligence jobs of creating the ideal ecosystem that facilities Machine Learning initiatives.
A data scientist is entrusted with the job of understanding the entire data ecosystem of a business, guide at what data should be collected, design and develop decision systems based on statistics, Machine learning and AI. Drawing up predictive data models based on historical data and creating machine learning models for learning from massive data sets. Data scientists typically are expected to have a strong foundation in computer science, statistics and mathematics. To be able to put their knowledge from statistics and mathematics spun around machine learning algorithms, data scientists also are expected to be good at programming, especially the ones that are specifically curated with efficient data structures, like Python and R.
Data Science lead is a role that leads the data science team from the front, providing direction as well as managing resources. The data science lead is expected to understand all the nuances of a data scientists’ job, while also understand the overall requirements and direction of the AI project.
The AI lead will interact with the data engineering team on various requirements of the data science team in terms of what data to capture, data sources, access to them. It is obvious that the AI lead is the link between data engineering team, the data science team and the management. The AI lead will set priorities for the data science projects, review progress and communicate findings to the senior management.
AI Research scientists, work on research teams developing new algorithms and products, constantly improving the efficiency and impact of a product. These folks are involved extensively in applied mathematics, statistics and machine learning. Typically, research scientists are expected to have a strong academic background and possess a PhD degree in mathematics or computer science.
The degree proves their ability to do research independently and be able to publish a white paper on their findings. AI research scientists are usually hired on the R&D wing of highly competitive industries like the consumer electronics industry, where there is a constant drive to churn out something new in each succeeding product.
A robotics scientist is a role which identifies all tasks that are repetitive and mundane and, in some cases, skilled and prepare a machine to the same tasks without any human intervention. Aspects of AI will need to be employed to identify the specific stimuli and conditions within the work environment and carry out the necessary tasks. Robotics scientists, design, test and deploy self-aware machines that carry out a specific task.
There is a special kind of robotics that is taking over the world, RPA or robotic process automation, which identifies mundane tasks involved in backend jobs and putting in a robotic solution that completes the tasks on a desktop machine without any human intervention. A simple example robotics at work is that of a robot on an assembly line in the car manufacturing industry and a complex example can be that of driverless cars. Robotics scientists are core engineers, typically holding a degree in computer science or robotics.
An AI Data Analyst is a role that performs data cleaning, data mining and data visualization and interpretation. AI Data analysts are typically Computer Science or Mathematics graduates with deep knowledge of database systems, data querying techniques, data cleansing methods through use of tools and programming languages like Python or R. A good knowledge of statistical analysis is also required in many cases.
Almost all major businesses in the IT industry are trying to provide solutions that are AI enabled. To give you an idea, there are even AI enabled farming solutions in the market today. Here is short list of companies that use AI in their products to stand out from the rest in the market.
Amazon, Apple, Google, Facebook, DataVisor, Casetext, Deepmind among many more.
As long as there is data around a process or task, which is inevitable and the process of collecting this data is not prohibitively expensive, an AI solution to the problems faced in traditional methods is always a possibility. AI in today’s context requires massive amount of data to ensure machines can learn from them and perform tasks as accurately as possible. Here are some of the industries where the role of AI is much more evident than others.
Healthcare – New and quick methods of diagnosis using AI help in reducing the time required for testing and diagnosis from days to just minutes.
Education – Education online and offline becomes more immersive and of much greater value with the use of AI.
Agriculture – AI can help identify the right practices to extract the best possible yield from a cop or identify the right crop based on changing weather conditions.
Banking – Online banking with improved assistance and a personalised banking experiences is now possible with AI.
Online Retail – With product recommendations AI has already become an indispensable too in the online retailing industry. AI is now also used to personalized shopping experiences based on face detection.
AI is the future technology available to us now. AI is rapidly evolving with a greater number of research and development teams driving innovations. Artificial intelligence jobs are in vogue and growing in demand. Artificial Intelligence jobs salary being on the higher side, are one of the most sought-after professions in the IT industry. Due to the evolving phase of AI, the future for AI looks promising with a stable growth in demand over the next couple of decades.
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