In the ever-evolving world of technology, some individuals stand out for their ability to not only lead groundbreaking advancements but also evaluate them on a global scale. Nitin, a thought leader in AI and Machine Learning (AI/ML) at Meta, shared insights from his work, including an illuminating talk at the System@Scale conference and a published blog titled “The Evolution of AIOps at Meta: Beyond the Buzz” last month.
He has been on the panel to judge technologists and companies across the world given his expertise. With a distinguished record as a judge for numerous prestigious tech awards, Nitin’s contributions to the field are nothing short of extraordinary.
In this TechBullion interview with Nitin Gupta, Engineering Manager at Meta, we get insights into his inspiring journey, and how he thinks about the future of AI & ML.
Could you tell us a bit about yourself?
Nitin: I have worked in the technology space for over a decade. I grew up in India where my interest in technology took me to studying Computer Science at IIT Guwahati.
I’ve had the opportunity to work at several companies, including Adobe, AWS, and Meta. Over the last 5 years, my area of focus has been in advancing AI & ML.
Your career has led you to a leadership position at Meta. Can you share your path to becoming an Engineering Manager?
Nitin: I started my career as a software engineer at Adobe, and over the years, as I transitioned to AWS and Meta, my role evolved into a tech lead overseeing large projects. When I encountered the challenges of AIOps and the need for more efficient investigations, I felt compelled to take on a larger leadership role by bootstrapping and growing the team. This experience taught me how gratifying it is to make an impact on people while advancing technology and delivering significant value to the business. I’ve successfully scaled the team from a handful of individuals to a self-sustainable business unit, allowing me to broaden my impact alongside my teams.
What motivated you to solve the problem of AIOps?
Nitin: I witnessed the complexity of large distributed systems during my time at both AWS and Meta. As these systems grow alongside the scale of the companies, it becomes increasingly challenging for engineers to debug issues quickly. I experienced this firsthand as an engineer, and I heard similar frustrations echoed by multiple teams across the organization. This common challenge underscored the need for more efficient solutions, which motivated my focus on AIOps and improving investigation processes.
What challenges did you face during advancement of AIOps at Meta and industry at large?
Nitin: As I mentioned in our talk, one of the primary challenges we faced was that AI for Ops was still in its nascent stages when we began our journey. We were operating ahead of the industry at our scale, which required us to pioneer solutions without established best practices. Additionally, Meta’s systems have evolved significantly over the years, and there was a rich historical context that needed to be understood and adapted for AI integration. This complexity meant that we had to navigate not only the technical aspects but also the organizational culture and legacy systems, ensuring that our AI solutions were relevant and effective within the existing framework.
You have also been involved in judging innovation for global awards including the Cloud Awards and Globee Awards. How did you get involved in these?
Nitin: My involvement in judging global awards stemmed from my industry reputation and previous recognition for my work in technology. As someone who has led significant innovations in this area, I was invited to evaluate and recognize other pioneering efforts in the field.
As a judge for multiple prestigious awards, what does your role entail?
Nitin: At the Cloud Awards, I serve as the Lead Judges and AI/ML Expert, tasked with evaluating cutting-edge innovations. It’s about understanding which solutions will have the biggest impact globally and recognizing organizations that are pushing the boundaries of what’s possible with AI. With the Globee Awards, I’ve been responsible for reviewing nominations for companies, CEOs, and leaders driving technological disruption. It’s fascinating to see how tech leaders are leveraging AI, cybersecurity, and digital transformation to make a real difference.
Q4: What do you find most challenging about evaluating these innovations?
Nitin: The biggest challenge is distinguishing between projects that are just trendy and those that represent a fundamental shift in technology and user experience. Many submissions are highly technical, but you have to dig deeper to understand the real-world applications. What excites me is when a technology not only solves a current problem but also has the potential to change how entire industries operate.
What advice would you give to those looking to innovate in AI and technology?
Nitin: At Meta, we have a saying- “Focus on Impact”. This has resonated with me throughout my career. Always ask yourself: How can my work create a meaningful impact? It’s easy to get lost in building technology for technology’s sake, but the real value comes when your innovation has a tangible, positive effect on the world. Once you get that clarity, you not only innovate but also give your team a tangible goal to work towards.
Thank you, Nitin, for sharing your experiences and insights with us. Your contributions to the field and your role in judging global awards are truly impressive. We appreciate your time and the valuable perspectives you’ve provided.
Nitin: Thank you for having me!
