NVIDIA Deep Learning for Genomics interview questions
based on 1 rating - Updated Mar 11, 2019
Averageinterview difficulty
Very positiveinterview experience
How others got an interview
100%
Employee Referral
Employee Referral
Interview search
1 interviews
NVIDIA interviews FAQs
Deep Learning for Genomics applicants have rated the interview process at NVIDIA with 3 out of 5 (where 5 is the highest level of difficulty) and assessed their interview experience as 100% positive. To compare, the company-average is 58.1% positive. This is according to Glassdoor user ratings.
Candidates applying for Deep Learning for Genomics roles take an average of 28 days to get hired, when considering 1 user submitted interviews for this role. To compare, the hiring process at NVIDIA overall takes an average of 25 days.
Here are the most commonly searched roles for interview reports -
I applied through an employee referral. The process took 4 weeks. I interviewed at NVIDIA in Jan 2019
Interview
I first did a general, non-technical phone interview where I shared my experience and learned a bit about the Deep Learning for Genomics team. I then had a coding interview - pretty simple questions where I had to optimize runtimes of standard algorithms problems. Finally, I had a deep learning-specific interview where I described the technical details of my projects and was also asked theoretical DL questions.
Interview questions [1]
Question 1
How does batch normalization improve training of neural networks?