Pros: Great work-life balance at the company.

Cons: Not too many machine learning opportunities.

Pros: Great company culture and growth potential.

Cons: Work-life balance can be off sometimes.

Pros: The compensation and benefits package is good.

Cons: The work environment at the company is very problematic, characterized by poor management, office politics, and a complete disregard for engineering quality. 1. The biggest issue is the layer of middle managers, who appear to be promoted on tenure or political alignment rather than leadership skill. They are fundamentally untrained in managing people, offering technical mentorship, or protecting their teams from unrealistic demands. Their primary function is to act as project trackers, pressuring engineers to close tickets without understanding the technical trade-offs. 2. Career progression is not tied to merit or quality of work, but to visibility and internal politics. Decisions are made in back-channels, and there is a sense of favoritism. This creates a toxic, low-trust environment where teams are siloed and collaboration is non-existent. There is more effort spent on managing "perception" than on solving problems. 3. Quantity-Over-Quality Engineering Culture: The engineering teams are run like a feature factory. The only metric that matters is closing the ticket and fast release. There is no incentive to follow good engineering practices. Code Quality: The codebase is a direct result of this. It is brittle, unmaintainable, and drowning in technical debt. Attitude: Engineers are not rewarded for writing clean, scalable code; they are rewarded for speed. This has cultivated an attitude of just "getting it done" and moving on, leaving a mess for the next person.