Pros: Work-life balance is phenomenal. Good compensation and general benefits package. PTO policy is incredibly generous (along with other days off/learning days). Great senior leadership.

Cons: High turnover. Consistently, work could be more interesting. Culture is team dependent.

Pros: Strong enterprise DevOps infrastructure. Good for early careers (one to two years) out of college.

Cons: Here is the reality of being a machine learning engineer at C1, despite all the social media marketing: you are rebuilding a tool that readily exists in commercial and open-source projects, which no one else uses within the company, except the MLEs who are building it, in order to justify continuing to build it. At the end of the day, you are reproducing an overengineered solution, which is also (in-part) intended to remove the need for your role (and data scientists). Modeling experience is largely non-existent since your time is best spent reinventing the wheel. Furthermore, you are also going to end up in effectively the only MLE org within the company, which also has one of the worst happiness and management cultures within all of Capital One. Prepare to spend every day working with mostly arrogant and unpleasant (to put it mildly) managers, who lack tech experience in many instances, while privately commiserating with coworkers in Slack. If you have experience elsewhere, you will be amazed to see such joyless teams.

Pros: Great opportunity to work on wide areas of DevOps and not have to stick to any one tool. Great friendly people to work with.

Cons: Lack of job security and constant changing of directions.