Why I Joined Scale
by Eugene Fratkin on January 15th 2019
The Bay Area is the densest area in the world for high-tech job opportunities. Why else would so many people brave the sky-high real estate prices and regular wildfires to live here? I was extremely fortunate to be faced with the Bay Area’s abundance of technology jobs when I thought about possibly changing careers. However, with many potential factors to optimize for and even more companies, it was easy to get distracted during the search. Some basic things to consider:
- Domain: Do you understand the company’s domain, and are you genuinely excited to learn about it?
- Business model: Do you understand the company’s business model, and how does the road ahead look?
- Role: What duties does the potential role entail? Are you being realistic about the day-to-day tasks that it requires?
- Company trajectory:
- Does the company show a promising trajectory and clear ways to mitigate risks?
- As a third party confirmation of your personal read, does the company have reasonable investors and a healthy financial state?
Since all of these factors are important, I spent time formulating my own opinion about each of these factors.
At the same time, I am joining a company in a technical leadership role, and there are considerations other than the company’s story and potential success that are critical for me. Many companies have a credible product vision that could resonate with the market, and a few of them will indeed be successful. I did a PhD in machine learning (ML) at Stanford because I strongly believe in AI’s impact and its increasing relevance. It’s very important to me to stay current with its applications and technical evolution. Thus, I wanted to choose a company not only with a potentially successful business, but one that had technical challenges relevant to my ML interests.
Machine learning and deep learning are today’s trendy buzzwords. While their technological importance is not overstated, these two terms are overused in marketing. Companies go out of their way to make it sound like doing research in ML is their core work, but I’ve found that most of the time it’s only aspirational. So, I dug deeply to understand what is actually critical to make Scale successful. There are indeed deep learning problems that are critical to the operations of the company, but the universe of technological challenges is far broader. It was not until I had more conversations with team members that the importance of game theoretical research to the success of the incentives or the importance of ML-driven simulations became clear. There are many interesting problems to be solved with a small engineering team, and this makes for an exciting challenge.
Building a startup is a unique experience; it’s very different from operating within a well-established corporation. For someone new to a startup world, it may sound crazy that Sequoia Capital was willing to let my friend and me, with little experience after grad school, build and run a company. However, it makes sense - if you spend years in an established company, you quickly hit a point of diminishing returns in terms of gaining the skills relevant to early stages of a startup.
During my time in the military we had a similar realization: spending too much time in the infantry does not increase one’s chances of becoming an effective special forces operator. I know firsthand it is exciting to see a startup grow and morph, if you have the right team with you during the process.
As I got to know the Scale team over a series of meetings, I noticed many came from the typical backgrounds one associates with competitiveness and achievement, such as top schools and high honors from academic competitions. This seemed to foster a general attitude at Scale that no problem can be too hard or too unfamiliar to solve with enough hard work. I think there is no better way to grow professionally than by surrounding yourself with a highly capable and intellectually engaged team.
However, individual capability is just one of many traits of an incredible team, and an incredible team is what makes an incredible company. There is a saying that “people join the company, but leave the team” – while one joins a company because of the company’s past success, one departs a company due to the state of the team. I think this latent variable is team dynamics, which strongly influences how much one will enjoy the work and how well company is able to execute. During my interviews with Scale, I felt that the Scale team was well-fused; they were focused on execution, close-knit, and excited about the mission and the product.
Fortunately, a couple of meetings into my engagement with Scale, the opportunity kind of fell into place. I was talking to a friend, and she asked me about the state of the conversations.
“I think I would like to join,” I said.
“Wow! Really? So quickly! There’s no offer yet? Have you talked to investors? How can you be sure so sure?” she replied.
“Those are technical details… I think I can figure those out.”
And that was that…