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 pay and benefits. The company also invests heavily in tech and machine learning.

Cons: There's simply a lot of bureaucracy and layers of middle managers. If you're a builder at heart, you'll be frustrated quickly since things move very slowly. Also, career advancement depends mostly on the ability to gain visibility with higher-ups rather than actual performance and contribution.

Pros: Good people, good pay, good tech.

Cons: There is no stock compensation package like in big tech.