There is a requirement for a skilled workforce and companies in MLOps – How important do you think is India’s role in producing a skilled workforce and niche MLOps companies?
Harsh Marwah, Chief Growth Officer at iValue InfoSolutions
“MLOps, in layman terms, is Machine Learning Operations. Organizations across the world have realised that data holds the real power and, the right use of data helps them leverage the gaps in the market and set themselves apart. Now, data scientists are needed to manage data and the operations team is needed for the right development, but to take the best advantage of both and make them work in sync, we need MLOps! India has been advancing its expertise in terms of AI/ML and even encouraging more data scientists to come into the foray. But, for the mission of data protection or data management to reach near-perfection and, be well intact to be implemented successfully, we are in dire need of MLOps scientists.
As per a report published by LinkedIn in 2020, the world has seen, in just four years the hiring rate and demand for MLOps specialists grow by 74%. In the coming days, as there is an exponential increase in data being generated, the demand will certainly increase for MLOps specialists more than ever and, I believe that India and its start-up culture has the potential to make use of the demand. Any software engineer, with the right guidance and training, can be moulded into an MLOps engineer. With young professionals entering the industry every year and senior employees already a part of the new transition, organizations need to make use of this opportunity and set out in a new direction, where India can be leading the world in this technology. With the right skill set India can certainly set a new precedence.”
Adrian Johnson, Director – Technology at TechnoBind
“Nowadays, one of the most buzz words is Devops and the technologies around DevOps. However, there is another technology which works in a similar fashion i.e., MLOps means Machine Learning Operations.
MLOps is the communication between data scientists and the operation or production team, it is deeply collaborative in nature designed to eliminate waste automate as much as possible and produce richer more consistent insights through machine learning. Now machine learning can be a game-changer for business which is obvious but without some form of systemization, it can develop into a basic academic experiment. MLOps brings business interest back into the forefront of your ML Operations where ML experts and data scientists work through the lens of an organisational interest with clear direction and measurable benchmarks. Hence, MLOps is primarily used for automating the lifecycle of AI projects.
To have MLOps effectively working in an environment, there is a need for a skilled workforce and hence need companies as well who can deliver automated AI projects.
In India, the companies are working on DevOps and producing a skilled workforce around DevOps by providing sufficient training to learners. Any point of time, leaners would encounter to data science while working on DevOps and require skills towards MLOps where they require to deliver the AI projects and need tools to automate the lifecycle of those projects. There are such trainings available in India where learners can learn the technology around MLOps and can deliver for the same.
Since AI is the future of technology and MLOps automates the lifecycle of AI projects, India would need to produce highly skilled people and companies in MLOps to stay in the race of technology.”
