Early Career People Should Consider Fast Growing Startups In Emerging Technologies

There are some opportunities to work at the intersection of technolgoy and doing good, but not enough for the many promising early career people. Another option that I don’t think gets considered enough is to work at a fast-growing startup in an emerging technology (e.g. robotics or NLP), where one can often have much faster skill development within a couple of years. By fast-growing startup, I mean a company that seems decently likely to be one of the top 20 highest valued startups founded in a given 5 year period.

Claim: it would often be a better long-term career bet to work at a fast-growing startup than to work at a nonprofit that doesn’t seem likely to be high impact or have high potential for individual growth.

The three main benefits from fast-growing startups are that the company’s growth leads to greater responsibility earlier, you can work with very competent people and develop a better bar for excellence, and that working on the edge of technological developments gives you insights into how the world will change over the next decade.

Aurora, a now-public self-driving car company, had 30 employees when I joined, and about 300 when I left two years later. Six months after joining, I became a project lead for a team of 5 engineers on a high priority project. That opportunity was mostly due to the company needing leaders to keep up with our growth and my generalist skills making me not-awful at the role. That experience taught me a lot about leadership, management, and long-term engineering projects, and it seems like this type of experience is much more common in fast-growing startups. In contrast, nonprofits often grow slowly or don’t grow at all.

An additional benefit is working with very competent people and getting a sense of what a highly successful company looks like. It’s useful to have a well-calibrated bar for who you should work with in the future and who to hire – I think it would be pretty valuable if more people trying to do good had well-defined standards of excellence. To quantify this, I think I probably worked with at least 5 of the top 100 people who have worked on self-driving cars in the past decade, and at least 15 people that could get hired to lead a team at basically any self-driving or robotics company.

It’s also useful to see trends in fast-growing startups to understand how the world is changing. At Aurora, I learned about how people are thinking about ML engineering and deploying ML products, and which parts of the ML industry were real or all hype. Learnings on the front of developing technologies seem a lot more useful for doing impactful work later than learning about random web apps because the learnings are more applicable for doing good in the future (e.g. AI research).