ML learning has become prominent in areas such as customer insight and personalization, operational efficiency, fraud detection and security, customer service and support, sales and marketing, HR, product development, financial forecasting and management.
ML engineers, data scientists, AI research scientists and product managers are part of the roles that are seeing a surge in demand.
Om Prakash Shanmugam, senior vice president of Engineering, Videooverse, says there are many opportunities for mid-term career experts looking to switch to the role of machine learning. Deep technical expertise has been a prerequisite for starting AI/ML, but recent advances have made democratizing into this field, allowing individuals with basic knowledge to pursue a high-demand role, he explains.
Rapid engineers, data scientists, AI creative professionals, data annotators, and AI safety engineers are some of these in demand roles. He suggests the wage structure of these roles, he says, to be between Rs 2.5 and 100,000 a year, depending on his experience and expertise.
Skills for an ace for smooth transition
For a seamless transition to the role of machine learning, Korla says individuals need both technical and non-technical skills. These include proficiency in programming languages such as Python, R, and SQL for data manipulation, building data science models, and performing exploratory data analysis. Apart from these, machine learning frameworks such as Tensorflow, Pytorch, Keras, expertise in data handling and processing using tools, and a powerful foundation of statistics and mathematics are extremely useful for understanding and developing ML algorithms. Being familiar with cloud platforms and MLOPS tools is important for deploying models and managing data at scale. Prakash's opinions, mathematics proficiency, logical problem solving, and reasoning are essential to mastering the concept of ML. Also, since most ML's responsibility involves data processing, the ability to use Excel to calculate numbers and extract insights is important. Individuals can also learn programming languages such as Python and SQL for complex analytical and data manipulation tasks. Strong English skills are essential for roles such as rapid engineering and AI creative professionals, he adds.
Courses to pursue
The importance of continuous learning and proficiency cannot be overstated when it comes to career advancements. To play the role of machine learning, Prakash says there are many courses and tutorials on platforms such as YouTube, Udemy and EDX. However, we recommend Deeplearning.ai's “ChatGPT Prompt Engineering for Developers” and OpenART.AI's “Prompt Book” especially for those interested in rapid engineering. Those planning to learn how to build advanced AI models should start with Fast.ai courses and Realpython.com for Python basics.
ML mid-career freelance opportunities
In the machine learning industry, there is a high demand for freelance and contract workers, particularly in the role of mid-term personnel, Prakash says.
He said advances in AI have increased the need for freelance ML engineers. Currently, over 76% of Indian B2B and B2C companies are developing AI-powered solutions, driving the demand for skilled talent in such roles.
To gain freelance opportunities, individuals can check out online platforms specializing in freelance machine learning opportunities, such as Upwork, Freelancers, Guru, and AI-jobs.net. Such a platform connects skilled professionals with companies seeking to leverage AI and ML expertise on a freelance basis, he adds.
