Joining a Startup vs a Big Company
The ever-alive dilemma of whether to join a startup or a big company has been a very active topic of discussion in my student circle in the last few months (graduation time!). In this post, I write about my personal views on when it can make sense to choose a startup over a big tech company and the various tradeoffs associated with the decision.
The Importance of defining priorities and risk appetite
Let me say this upfront. Like most other things in life, there’s no single golden rule that can help make this decision easy. But before jumping into the chaos of all the different factors which can affect this career decision, I find it helpful to reflect and ask myself what am I trying to fundamentally optimize for when making this decision. In regard to the startup vs big company decision, this can be an ordered list of several things like maximizing learning opportunity, minimizing regret, maximizing money, maximizing work-life-balance, maximizing the possibility of exploration, maximizing flexibility, minimizing effort and so on. All these appear in different proportions in different kinds of jobs and the amount of accepted variability in each forms the perimeter of risk you’re willing to take across each aspect. To take a few specific examples from real life, a lot of friends from my machine learning/ computer vision circle decide to join/not join a specific company because of reasons like “I want to stay in the self-driving industry as it’s hot right now”, “I can afford to work for less money on more interesting problems at this stage of my life”, “I want to stay in the Bay Area as it’s easier to switch jobs”, “I want to work on research” or the good old “I want to earn a shit ton of money and xyz company is paying a lot!”. All these are examples where the people were optimizing for a set of things they wanted to prioritize in life. This is a very good thing. Being clear about what you want from life might not give you what you want. But it can often give directions to your decisions and limit blind fluctuations in the end result.
Before giving my list on how one might evaluate startup vs big-company job opportunities, it’s critical to note a few things. First, startups come in different flavors. Not all of them have a hippie hacker culture, not all of them pay badly, not all of them are doing disruptive work, not all are cradles of rapid learning experience and most of them will fail at whatever they’re trying to do. They come in different sizes, very different cultures, different future prospects and different opportunities. It’s tough, but necessary to evaluate them individually. The points below only apply to startups where these characteristics exist. Also, I recommend you read this blog post by Dan Luu for an interesting point of view.
Choosing between a startup and a big company
There are countless stories on Reddit and Blind about software engineers in FAANG questioning their work life satisfaction after years of work in big tech. Sometimes, writing a load balancer for some internal platform or making APIs for a nondescript feature in an app, though a useful component for the company, is not of a lot of personal value to one of the individuals working on that team. In a big company with high hiring volume, you’re always functionally dispensable and the impact you make to something in the real world can sometimes be very low and more importantly is often opaque even after accounting for the fact that larger companies serve millions of users. Amazon sometimes has multiple teams competing for the same product and after working on a project for months a lot of your work might not even see the light of the day. However, depending on the size and nature of a startup, you can feel the tangible effect of your work. My friends interning at bigger self-driving companies like Uber ATG had a harder time knowing their work would be deployed and of use to anyone than the ones interning at smaller companies like Aurora and Nuro where they saw their work being adopted and tested while they were still interning. I myself had similar experiences with PathAI even though I worked on research projects which are even less prone to getting deployed. All good startups aim to add value to the society and it’s a great feeling to go back home knowing you affected real change that was visible to the company and even perhaps to the society. Of course, staying clear of startups that don’t add value is critical here (smart flip-flops and smart juicers! Give me a break).
Learning opportunities & career development
There are some things smaller startups can be great at. They allow you to have a more holistic view of the running of the whole company. They also allow you to build from ground up and take more initiative towards high impact projects at a younger age than what a large company would. Anyone having future entrepreneurial ambitions can extract a lot of learning from such startup experiences. Another great thing which lends itself to faster career development is the lack of regimented structure and bureaucracy in smaller companies. It’s possible for people to grow career-wise in larger companies by focusing on metrics which might not correlate directly with what was beneficial for the company or the learnings of an individual or teams. However, in smaller companies, this alignment is more easier to evaluate. Another area in which I’ve read contrasting viewpoints is startup vs big-company jobs for recent graduates. On one hand, larger companies have streamlined pipelines and mature tools, best coding practices and stronger code-review culture and hence lead to building of better fundamentals in recent graduates. Startups often are fighting for survival/growth and hacking your way to a solution and ignoring best practices makes partial sense for them. On the other hand, startups can often rapidly shift to new tech stacks, adopt new technologies and are less tied to massive pipelines and structures which help scale the processes for larger companies but at the same time make them slow and harder to change. A friend recently pointed out that his team at Microsoft took half a year to migrate a small tool to prevent deprecation of certain services. Another friend told me about how a team at Amazon had to wait for 2 months before trying out a new set of machine learning algorithms in their workflow because the pipeline for it was still being built so that the company could scale it easily once done. Things like these drastically slow down your own learning ability.
Startups have it hard when competing with big tech for salaries, specially as you go towards more senior positions. This is the reason they complement the lower salaries with equity or stock options. However, it’s worthwhile to evaluate the chances of the startup you’re considering to join making it big and more importantly your own chances of offsetting the lower pay with a higher, but risky payout in the future. There are so may factors here that it’s easier for me to point to this and this blog post to see two slightly different points of view on the topic of whether the stocks in a startup is worth the risk of accepting lower money. Also see this Reddit post on evaluating startups offers. In general, from the statistics I’ve seen being thrown around on the internet, accounting for the risk of a future liquidity event and adjusting the possibility of extremely high payouts for early startups employees, most startups are certainly less attractive options if money is a high priority item on your list. But if you have faith in your ability to judge the health of a startup, the problem it is solving and its value to the market and finally your own circumstance-dependent evaluation of your risk appetite, it might be reasonable to choose startups for money.
I have pointed out some reasons where a startup is more likely to work out better for you than a larger company. But there are so many individual data points all across the spectrum and this analysis needs to be done on a case-by-case basis. Many large companies have small teams which give a lot of similar benefits as startups without the risky downsides of it. Most big tech companies today have specialized teams working on cutting edge areas like machine learning, NLP or blockchain and the high impact of the projects and the rate of learning is as good as a startup without the need to compromise on money. However most non-senior roles in big commpanies will never be able to allow exposure to self-initiated, high impact projects. People themselves have different strengths and not everyone can be successful in a startup environment. All this taken together means that the final decision of how to choose a place to work depends heavily on the specific options you have and your own interests and abilities.