At 8am, Saurab Agarwal flips through the latest artificial intelligence (AI) research papers over coffee, trying to keep up with the dynamic field.
Agarwal, a machine learning (ML) engineer at India-based AI platform company MavQ, has seen AI development unfold since the day he stepped into the technology.
A computer science graduate in Jaipur, North India, Agarwal started playing with the power of data during a full-time internship in data engineering and cloud. He soon found himself digging deeper into data analytics, building his pipeline of data for ML models.
Under the guidance of mentors such as Salesforce pioneer, Mulesoft specialist, and multi-cloud expert Gaurav Kheterpal, and with the help of the AI community, Agarwal honed his craft in ML modeling.
He spent over two years learning how to develop ML models from scratch and then got the hang of deploying ML models. Besides scaling models, he is also responsible for models for converting paper documents to digital formats while working on deep learning. In parallel with his work, he has completed executive courses in AI and ML at the Birla Institute of Technology in Pilani.
“The sheer joy of knowing what can be done with data is exciting. During the previous IT boom, we had a vague idea of what could be done, but back then data was limited. Now, with data consumption growing exponentially, our models are simple and resource-friendly,” says Agarwal.
“We believe there is a lot of room for MLOps in the next five years.” [machine learning operations] And commercialization of the model. It is very rewarding to be involved in scaling models at my company and ensuring that they are not bulky or expensive. Staying on top of costs and competitiveness makes this job exciting every day. ‘ he added.
Machine learning can be a high paying career in India. According to Agarwal, the average ML engineer’s salary package could range from Rs 100 crore to Rs 200 crore for him. 1.5 to 20 million rupees (US$18,000 to 24,000 USD) per year, higher level domains cost him 20 million rupees. Annual income of 6 million to 7 million as skills improve.
Besides MLOps, which involves productizing and optimizing ML models, applied ML and advanced modeling are also areas of interest. But Agarwal says people who are articulate and sharp about their particular areas are most effective.
“Anyone who is good at software engineering can easily get in. People need to be comfortable and aware of data. Awareness and a knack for how data impacts businesses is paramount in this profession,” he says.
“AI is so vast. Understand its own domain. needs to adapt to AI and strengthen us, it’s that simple.”
Saurab Agarwal, MavQ
He also points out the importance of explainability and modeling ethics: And recognize the impact. “
Agarwal spends most of his day leading a team of 15-20 people to bring ML models to market. He is also involved in benchmarking models against top models in the industry. “We have to constantly check how accurate, how good and how fast we are compared to the best in the industry. ,” he says.
Agarwal believes AI will only amplify the potential of data in business in the future. “As models and deep learning improve, we will see AI perform to its advantage. To do that, it will be important to scale and run models while facing the ‘black box’ problem,” he said. , he added, noting the challenge of understanding how decisions are made by some complex AI models.
Agarwal usually ends the day with a jog or a game of badminton. On the track, he knows when to sprint and pause, as any good AI professional should be.
His advice for aspiring ML and AI is twofold. It’s about choosing your domain well and having an innate love for your data. “AI is so vast. Understand its own domain. needs to adapt to AI and augment us, it’s that simple,” he says.
