Pros
1. High growth potential: Smile Identity is a startup, which means there is a lot of potential for growth and expansion in the future. As a machine learning engineer, you will be able to contribute to this growth and have a direct impact on the company's success. 2. Innovative technology: Smile Identity is focused on developing innovative technology in the identity verification space. As a machine learning engineer, you will have the opportunity to work with cutting-edge technology and contribute to its development. 3. Positive social impact: Smile Identity's technology has the potential to make a positive impact on society by improving access to financial services and reducing fraud. As an employee, you can feel good about contributing to a company that is working to make a positive impact. 4. Collaborative work environment: As a startup, Smile Identity likely has a collaborative work environment where employees work closely together and have the opportunity to make a significant impact on the company's direction and success.
Cons
Job insecurity: Probably because Smile is a growing startup, but I have noticed a high level of job insecurity and constant lay-offs especially in recent times and among junior employees. The Artificial Intelligence and Machine Intelligence department, where I currently work, offers little room for junior employees to grow professionally. The department is highly competitive, and individuals are primarily focused on completing their own tasks. Despite the presence of both senior colleagues who can provide guidance to junior colleagues in need of assistance, it is often not the case. It can be challenging to progress on tasks without the necessary support. This lack of assistance results in being stuck on tasks for extended periods, hindering progress that could have otherwise been achieved with timely help from others. Point is everyone who is able to provide help seem too busy. High pressure: The pressure to succeed and grow quickly can be intense in a startup environment. As an employee, you may feel pressure to work long hours or deliver results quickly, which can lead to burnout or stress. That was hard to deal with. I've seen the company and various teams grow to this point which seem to have a better structure than when I first joined. Regardless of the substantial growth, it is sometimes a bit challenging to navigate day-to-day work. As a machine learning engineer, you may need to be self-directed and take initiative to make progress on projects.