Not many people do work hard, but it is worth it.
I applied to the San Francisco office. The process started with a screening phone call with a recruiter, then a take-home ML exercise which you have to return within 2 weeks, and finally a technical interview which has theory questions as well as som
1. Technical Assessment: NLP or CV toy project with a 7-day deadline. 2. Phone Interview: Very close to another interview resource found online. 3. Virtual Onsite (4 hours): I was asked to provide dates for the interview, to which I promptly replie
Take-home challenge: choose between NLP and CV, train a neural network, and achieve above some accuracy on a given test set. You can use open-source libraries, but you need to have some unique parts of your own. There's a penalty if you use models th
I applied to the San Francisco office. The process started with a screening phone call with a recruiter, then a take-home ML exercise which you have to return within 2 weeks, and finally a technical interview which has theory questions as well as som
1. Technical Assessment: NLP or CV toy project with a 7-day deadline. 2. Phone Interview: Very close to another interview resource found online. 3. Virtual Onsite (4 hours): I was asked to provide dates for the interview, to which I promptly replie
Take-home challenge: choose between NLP and CV, train a neural network, and achieve above some accuracy on a given test set. You can use open-source libraries, but you need to have some unique parts of your own. There's a penalty if you use models th