Throughout my career, I’ve been drawn to foundational challenges. The kind that, if solved right, can transform the biggest systems in the world. With each technological shift – web, cloud, mobile, and now AI – we’ve seen a new class of category-defining companies emerge. The web gave us Google. Cloud established AWS. Mobile unlocked Uber. Now, AI is reshaping the way we work, hire, and build. The next breakout companies will be born from this inflection point, and I believe Mercor is one of them.

When I was studying computer science at IIT Delhi, the internet was just beginning to take shape. I was captivated by how data moved through networks and what became possible when digital infrastructure connected people at global scale. That fascination led me to ONI Systems, where I worked on optical networks. The internet was growing faster than infrastructure, choked by bandwidth and throughput constraints, could keep up.

Two decades later, I see history repeating itself. The bottlenecks are no longer physical routers and fiber optics, but they’re just as real. Today’s AI systems are limited by three key factors: compute, algorithmic breakthroughs, and access to new, high-quality data. Foundational models have made astonishing progress, but unlocking their next phase of capability depends on how well we can guide and refine them with structured, domain-specific feedback from human experts.

That’s what drew me to Mercor.

Mercor is tackling one of the most important and overlooked infrastructure challenges of our time: how we evaluate and allocate human talent. We’re starting with AI labs because training frontier models demands the expertise of humans, like lawyers who probe reasoning, engineers who review code, and physicians who validate clinical outputs. Mercor matches these experts to projects and uses feedback to continually refine the matching itself. Place talent, observe outcomes, refine predictions—repeat. The result is a data-rich feedback loop that learns more about human performance in weeks than traditional hiring systems learn in years.

Observing Mercor’s early days, I feel a strong sense of déjà vu. I’ve witnessed rapid growth firsthand at Amazon, Google, Uber, Instacart, and Stripe. Each tackled foundational infrastructure challenges in their own domain. At Amazon, I had a front-row seat as AWS evolved from an internal platform to the backbone of the internet. At Uber, we started with a specific use case – ridehailing – and scaled it into a global transportation network. I still remember the mantra: make transportation as reliable as running water. At Google, the mission to organize the world’s information drove us to build systems that could scale with the internet itself. Similarly, at Stripe, we built programmable financial infrastructure designed to be global from day one.

At the heart of each of these companies was the same thesis. If you solve a foundational problem deeply, you don’t just build a product – you build a platform that reshapes entire industries. Mercor now fits that legendary lineage. But in an era when AI is reshaping the nature of work, I believe Mercor is seizing an opportunity far more consequential than any other: the market for human potential.

Currently, the broader labor market is fractured and inefficient. Candidates see only a fraction of opportunities. Companies rely on weak proxies like résumés. Mercor is building the most structured and comprehensive performance dataset ever assembled, allowing us to match any person to any opportunity with incredible precision. The engine that helps an AI lab hire 300 PhDs in a weekend will eventually power a global talent marketplace where every company can hire confidently and every candidate gets a fair shot. In the long run, I believe Mercor will redefine the endgame for human work.

Since joining Mercor, I’ve helped scale our systems from 1 to 100 million in payments volume in under a year. I’ve worked on the infrastructure that underpins large-scale evaluations and makes talent assessment fair and effective. It’s among the most complex and meaningful challenges I’ve taken on.

Mercor is already one of the fastest-growing startups in Silicon Valley history—and we’re just getting started. We’re hiring across engineering and operations. If you’re excited about shaping the future of work and building systems that unlock human potential, we’d love for you to apply at mercor.com/careers.