Pros
In a startup, you'll directly contribute the research outcome to product and moreover, revenue. Which means there are more chances to build an impact. Also in Text IQ, the working environment is pretty dynamic and at a fast pace, you can complete your work in your favorite working style. To propose new techniques and system is easy to be embraced as long as it meets the requirements. The opportunity to develop industrial level machine learning models both in supervised / unsupervised manner is a huge plus as a research engineer here. Immersed in cutting-edge research results and stay in touch with the research community is also part of the daily job here. The engineer/researcher peers are awesome. I enjoy the time collaborating with people here. And as the team grows we're bringing more FAANG company talents into our board. Pretty exciting.
Cons
Typical start-up growing pain --- dynamic goals, sometimes strict deadlines, and not so well structured management system The main engineer team is located in Vancouver which means communication is sometimes trickier for NY research/engineer peers.