Machine learning is gaining traction in areas such as customer insights and personalization, operational efficiency, fraud detection and security, customer service and support, sales and marketing, human resources, product development and financial forecasting and management, says Anesh Korla, EVP and COO at Encora in India.
ML engineers, data scientists, AI research scientists, and product managers are some of the roles seeing a surge in demand.
Om Prakash Shanmugam, senior vice president of engineering at VideoVerse, says there are many opportunities for mid-career professionals looking to transition into machine learning roles. Previously, getting started in AI/ML required deep technical expertise, but recent advancements have democratized access to the field, allowing individuals with basic knowledge to land in-demand roles, he explains.
Prompt Engineer, Data Scientist, AI Creative Professional, Data Annotator, AI Safety Engineer etc are some of the roles that are in high demand. Talking about the pay structure for these roles, he said it ranges from Rs 250,000 to Rs 100,000 per annum depending on experience and expertise.
Skills to learn for a smooth transition
According to Korla, to transition smoothly into a machine learning role, an individual needs both technical and non-technical skills. This includes proficiency in programming languages like Python, R, SQL for data manipulation, building data science models, and performing exploratory data analysis. Apart from these, machine learning frameworks like TensorFlow, PyTorch, Keras, expertise in using tools to work and process data, and a strong foundation in statistics and mathematics can be extremely helpful to understand and develop ML algorithms. Familiarity with cloud platforms and knowledge of MLOps tools can be equally important for deploying models and managing large-scale data. In Prakash’s opinion, proficiency in mathematics, logical problem solving, and reasoning are essential to master ML concepts. Also, as many ML responsibilities involve data processing, the ability to use Excel to crunch numbers and derive insights is essential. Individuals can also learn programming languages like Python and SQL for complex analytical and data manipulation tasks. He added that strong English language skills are a must for roles like prompt engineer and AI creative professional.
Courses to take
It can’t be overemphasized that continuous learning and upskilling are important for career advancement. Prakash says there are many courses and tutorials on platforms like YouTube, Udemy, and edX to land a job in machine learning. But for those specifically interested in prompt engineering, he recommends Deeplearning.ai’s “ChatGPT Prompt Engineering for Developers” and Openart.ai’s “PromptBook.” He adds that those who plan to learn how to build advanced AI models should start by learning the basics of Python with fast.ai’s course and Realpython.com.
Mid-career freelance opportunities in ML
Prakash said the machine learning industry is seeing a rise in demand for freelance and contract workers, especially for mid-level roles.
He said advances in AI have increased the demand for freelance ML engineers. Currently, over 76% of B2B and B2C companies in India are developing AI-powered solutions, increasing the demand for skilled talent to fill such roles.
To grab freelance opportunities, you can look into online platforms that specialize in freelance machine learning opportunities, such as Upwork, Freelancer, Guru, and AI-focused platforms like ai-jobs.net. Such platforms connect skilled professionals with companies looking to leverage their AI and ML expertise as freelancers, he adds.