Deep Learning Intern applicants have rated the interview process at NVIDIA with 2.5 out of 5 (where 5 is the highest level of difficulty) and assessed their interview experience as 75% positive. To compare, the company-average is 58.3% positive. This is according to Glassdoor user ratings.
Candidates applying for Deep Learning Intern roles take an average of 60 days to get hired, when considering 4 user submitted interviews for this role. To compare, the hiring process at NVIDIA overall takes an average of 25 days.
Common stages of the interview process at NVIDIA as a Deep Learning Intern according to 4 Glassdoor interviews include:
One on one interview: 29%
Drug test: 14%
Presentation: 14%
Background check: 14%
Skills test: 14%
Phone interview: 14%
Here are the most commonly searched roles for interview reports -
It is still in process, one week passed. I'm waiting for the result of the first round of interviews. The first round is main to describe the own research topics, will have some general questions.
The interview started with a resume deep dive followed by a short basic python coding test. Not leetcode based but more syntax based. After this we continued discussing a project on my resume in more detail.
Asked about the diffusion related project in resume: explain how diffusion work, explain how the scheduler affect the training.
Two coding problem: Write the conv2d function, write an attention module
Interview questions [1]
Question 1
explain how diffusion work, explain how the scheduler affect the training.
The interviewer starts with an introduction to the team and goes through the details of the project in the resume. You are asked to make connections between your experience and what the team is doing