Pros
1. They give you opportunities to do your own learning. The company is flushed with cash, so do not worry about not being paid 2. If you are an aspiring ML engineer who wishes to break into the field, this company is the perfect training institute to achieve your goals
Cons
1. Management doesn't follow what they preach. They said it is noble to disrupt the healthcare industry, but it seems they are just concerned with selling the product instead of improving it. 2. You have to learn everything on your own, it can be daunting if you do not have AI experience. 3. Only half of the company staffs are doing useful work. The other half seems to be a waste of resources. Apparently, they seem to be well connected people who pulls strings to get in without have to prove themselves. 4. Management hires people who fail the interview and missed out on good candidates due to their recruitment process. Hence, there's a lot of false positives in the company. 5. The tech stack which company uses is simply not scalable. Everything is just tensorflow and python. Of course we have the infamous internally developed tensorgraph (which nobody uses btw) 6. Management doesn't hear feedback and is thus incapable of leading the company. The sole reason why they survived till date is due to the hard work of the founding employees (you know who you are) and the deep pockets of the chairman. 7. If you are an ML engineer or data scientists, be prepared to not receive any guidance throughout your time in the company. The CTO will not be able to offer any form of advice or suggestions for your projects. You are on your own. 8. Company is stingy with bonuses and benefits. Also, living conditions are harsh in Beijing. 9. You will learn about game theory in the toxic environment because everyone is contemplating when to leave. You never know when your colleague is serving his or her last day. People come and go so often that it will blow your mind. 10. For experienced hires, this is the perfect place to stunt your growth. Join at your own risk.