Armed with almost $190M in total funding, Hyperscience has come close to doubling its team in 2020 and has goals to do the same in 2021. Maintaining that growth over the course of two years would be challenging for any company, but for one that’s on the cutting edge of machine learning and AI automation, nailing the hiring process, especially on the technical side, will be imperative.
For most companies, raising a $60M Series C round would signal an incredibly successful year, particularly in 2020. Not at Hyperscience. After that capital influx in June, the AI-based enterprise software automation platform was able to raise an additional $80M Series D four months later to become one of the highest-valued enterprise startups in New York.
Now armed with almost $190M in total funding, Hyperscience has come close to doubling its team in 2020 and has goals to do the same in 2021. Maintaining that growth over the course of two years would be challenging for any company, but for one that’s on the cutting edge of machine learning and AI automation, nailing the hiring process, especially on the technical side, will be imperative.
Enter Suren Hiraman, a longtime engineering manager who was hired as Hyperscience’s VP of Engineering in June. Suren, who has been working in or around machine learning technology basically since that became a thing, will help lead this team growth on the technical side.
The rare engineer whose career has placed equal importance on optimizing both people and machines, Suren got his first software engineering job in 1993 to do what he describes as low-level hardware programming. From there, he became a Big Four consultant and then worked for several early-stage startups, where he did the kind of data compiling and statistical patterning that eventually laid the groundwork for the prolific machine learning technology made at Hyperscience. Later on, he helped grow and manage technical teams at places like Salesforce, Spotify, and Namely.
These stops, while all very different experiences, have reinforced to Suren that the most important part of a company is not the technology or the product — it's always going to be the people.
“The key, above anything else, is that you not only have to hire people who align with what you believe are the dimensions of high-performing teams, but you also have to nurture them,” Suren said in an interview with The Org. “No matter what processes you put in place, no matter what organizational structure you put in place, none of them will ever be perfect. It always comes back to the people.”
Over the course of his career, Suren has grown to think of engineering leadership as three buckets. The first is technology, essentially being a leader who can make sure the internal and external roadmaps are aligned and realistic. Due to the nature of the field, Suren has found that many engineers can handle those types of responsibilities.
But the other two buckets, people and organization, have proven to be a little more complicated.
“It’s more rare to find technical managers and leaders who really want to embrace people and organization,” Suren said. “If there are fewer of those managers, employees then have fewer mentors to rely on to become good at managing people. What I've found over time is that, yes, I can trust other people to handle the technology side, but the need in a lot of organizations is more around the people and the processes.”
Why is that? Well, people are incredibly complicated. And hiring and motivating a team means having to constantly wade around in that complication. The reality, though, is that you can’t build a great product without understanding the motivations and emotions of the people building it. If engineers don’t know why they’re creating something, or don’t believe in its utility, the output of the whole organization will eventually slow to a crawl.
While knowing how to lead and organize differs greatly by the company, Suren has spent enough time studying people to feel that there are seven ways to successfully build a high-performing team:
This year has made some of the more personal parts of Suren’s job at Hyperscience little more complicated. He can’t run into employees in the hallways or create organic bonds over lunches and coffee breaks, though Zoom has helped with check-ins. Plus, he’s tasked with hiring almost 80 new team members in 2021, an incredible task even in a non-COVID landscape.
For Suren, though, the hiring process hasn’t changed. He starts with his seven fundamentals and then maps that onto his interviews, which he tries to make as natural as possible by allowing candidates to stumble and work through problems. Large-scale machine learning automation is complicated, and building those tools requires a team of innovative thinkers. Almost thirty years after his first software engineering job, Suren still knows it’s all about the people.
“I believe that the interview process is a very unnatural environment,” he said. “The risk of false negatives is much greater than the risk of false positives. People get nervous, people have different abilities to be able to represent themselves fully and truthfully. We have to thread the needle between getting the true signal that we need but also making it as easy as possible for the person to shine and represent themselves well.”
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