Pros: Great WLB, and it is fully remote. The teammates are collaborative and easy to work with.

Cons: Management changed requirements very frequently, which made it hard to align with stakeholders beforehand since they would propose something else in the middle of the process.

Pros: Most people I work with are wonderful: good collaboration, willing to spend time helping each other, and genuinely care about the mission of economic empowerment. The company has good compensation, especially for being remote-friendly. They also nail being "remote first" in terms of how meetings are set up, async collaboration standards, regular team gatherings, and more.

Cons: Unfortunately, the last couple of years have featured big layoffs and aggressive performance management, which has heavily targeted ICs while leaving top leadership untouched. Culture has gone downhill and is increasingly feeling political and toxic, with teams fighting over scope. The company is going all in on AI. All engineers are expected to use the tools constantly, and their AI token usage and PR counts are being tracked in dashboards. The most unfortunate part is that in the frenzy of chasing AI trends, leadership has completely lost touch with what customers and small business users want and need.

Pros: Some nice people trying to move the needle. Good company, overall goal. If you don't know anything about ML and want to be an ML engineer, they will hire just about anybody and give them a Sr. ML Engineer title. Got a physics degree? You are a shoe-in. Economics degree and one year at an "AI startup"? You'll be leading ML projects and a Lead Software Engineer.

Cons: Toxic middle management. No real experience in ML, but leading projects just because they've been at Square a long time (probably because no one else will hire them). Management is political; they will promise new features or lie just to put up roadblocks against other, more qualified teams that can deliver. The tech stack is an all-inhouse nightmare: "Let's build it all ourselves" mess. It's a bunch of engineers whose first answer to every question is, "Let's build something new," or maybe, if you're lucky, they are like, "Let's buy something new and then package a bunch of our own tech around it and call it a new project." Many of the projects are on the 4th/5th iteration of just the same old tired nonsense so somebody new can be a DRI. Instead of, you know, just using open-source tools and ML frameworks that already do what is needed. But there's no promotion or bonuses in making the right decisions in PIE. Maybe other parts of the company are better, but the PIE (ML Platform group) is career suicide.