There is a massive demand for skilled AI professionals right now in India, and there is a lack of talent that can fill these roles. 76% of companies feel this lack of talent is hindering their ability to implement AI. For working professionals looking to meet this supply-demand gap, it might be confusing to choose the right aspect of AI to specialise in, owing to the broad nature of this domain. So we’ve put together this list of the most impactful, high-demand roles that are available right now, as seen below:
This is by no means an exhaustive list, but a collection of roles that are most likely to be highly impactful on the growth of the AI industry, as well as offering high growth opportunities for professionals engaging in it.
Data Science as a domain is almost as broad as AI and ML when it comes to the scope of implementation across different industries. Data Science is a combination of data inference, algorithm building and implementing technology in order to derive insights from a data set. Since it uses a fair amount of mathematics and statistics, there’s considerable overlap with Artificial Intelligence. Data Science is already a domain that has a lot of demand for professionals, so becoming a Data Scientist with a focus on AI would help professionals carve out a lucrative niche in both domains and build a rewarding career.
Data Scientist can be a very broad term that describes a host of functions across a host of different domains, but in this specific instance, a data scientist is responsible for the massive amounts of data that are required to build robust AI models. Their chief responsibility is analysis, that ranges from collecting data to manipulating to providing actionable insights. In most cases, data is unstructured and unsanitized, and the data scientist needs to be able to structure the data to make it processable by the AI algorithm. Any real-world application of AI needs high-quality and relevant data for it to deliver the expected results, and it’s the role of the data scientist to manipulate the data into a machine-readable format.
AI SOFTWARE ENGINEER
Software development is a crucial part of any company’s technology journey. Just as software engineers have been tapped to build various digital products in SaaS, Cloud, Social Platforms, e-commerce sites and so much more, someone needs to build AI products as well. Software engineering in the AI sector has just barely passed its nascent stage as new applications of AI are sprouting up all the time, so there’s a lot to learn, and consequently, a lot of growth potential as well.
The role of the software engineer is vital to the functioning and management of AI models and applications. Obvious as it sounds, the role of an AI software engineer is to build the AI models and the applications, where the AI architect will piece them together to form a working solution. Software engineers need to be proficient in the programming language of choice, along with a set of routines and functions, called libraries, that are used frequently.
Computer or systems architecture deals with the specifics of building systems, by defining the functions, organisation of components and the implementation of the system as a whole. As computer applications started becoming complex, systems architecture became necessary to address the complex requirements of modern applications, by integrating the software and hardware components effectively. In Artificial Intelligence, where the complexities are exponentially higher, architecture becomes crucial to build an effective AI model.
This is one of the most crucial roles to sustain an AI model, and the lack of AI Architects actually hampers the ability of companies to execute their AI models. An AI Architect is responsible for translating the companies business objectives to efficient and profitable AI implementation, so it’s a really high-impact role in a high-impact industry. They chart out the structure of the AI implementation and design how the different components of AI work together to deliver a solution.
AI MODEL TRAINER
Model Training is one of the core aspects of effective application of AI. Building the model is a challenging task, but model training helps to fine-tune the results to ensure a higher degree of accuracy. Until now, model trainers have worked with relatively simple algorithms, but the sheer amount of data that AI needs throws up a unique set of challenges. Model training is not just about feeding data to the algorithm, but also to ensure that the input data is relevant, free of duplicates and does not contain any other rogue data that could derail the model.
This role would overlap with the Software Engineer or Data Scientist, but as AI systems mature and become more sophisticated, AI trainers will grow into a specialised role where their sole task is to train AI models with preferred data that improves their overall accuracy and effectiveness. They usually do this by manually feeding the training algorithm with relevant data that improves accuracy and performance.
AI PRODUCT MANAGER
Product management deals with building, testing, managing and improving a digital or physical product. Product management includes planning, forecasting, production or marketing of a product at different stages of the product lifecycle. This role would have different responsibilities in different organisations, but the overall gist of the role is what we’ve just described. Product managers are an important part of any company, because products are usually the lifeblood of a company’s revenue stream.
It’s crucial to look at AI as a product rather than just as a supplementary service. The function of an AI product manager, as any other product manager is to be the point of contact for all teams, acting as a single point of contact for all stakeholders of the product. They are responsible for charting out the roadmap for the product and are involved in aligning the product development with the business goals of the company. They also take part in activities such as taking the product to market, collecting user feedback and converting them to feature requests, and much more.
If any of these roles interests you and you are looking for a way to launch your career in Artificial Intelligence and Machine learning, you can consider Great Learning’s Post Graduate Program in AI and ML that teachers learners industry-relevant skills through hands-on projects.