Pros: a b c d e

Cons: f g h i j

Pros: Many potential opportunities for growth.

Cons: Widespread usage of in-house frameworks

Pros: Pros: Cutting-edge work: I had the opportunity to work on impactful ML projects using state-of-the-art tools and models. The team is very forward-thinking and open to trying new techniques and ideas. Smart, collaborative colleagues: The engineering team is filled with talented individuals who are generous with their knowledge. I learned something new every week. Supportive leadership: My manager was approachable and invested in my growth. Regular one-on-ones, feedback sessions, and career development discussions were the norm. Learning environment: There was strong support for continuous learning – from access to conferences and courses to internal reading groups and tech talks. Work-life balance: Despite the fast-paced nature of the work, the company respected personal time and encouraged healthy work habits. Strong engineering culture: Code reviews, testing, and reproducibility were emphasized, which helped maintain quality and foster team-wide learning.

Cons: Cons: As with many fast-moving teams, priorities could shift quickly. It took some time to get used to the pace and ambiguity. Occasional cross-team communication hiccups, but leadership was aware and making improvements.