Glassdoor users rated their interview experience at NVIDIA as 100% positive with a difficulty rating score of 3 out of 5 (where 5 is the highest level of difficulty). Candidates interviewing for Sr. Machine Learning Engineer and rated their interviews as the hardest, whereas interviews for Sr. Machine Learning Engineer and roles were rated as the easiest.
The hiring process at NVIDIA takes an average of 21 days when considering 1 user submitted interviews across all job titles. Candidates applying for Sr. Machine Learning Engineer had the quickest hiring process (on average 21 days), whereas Sr. Machine Learning Engineer roles had the slowest hiring process (on average 21 days).
Here are the most commonly searched roles for interview reports -
I applied through college or university. The process took 1 day. I interviewed at NVIDIA (Toronto, ON) in May 2013
Interview
Applied during a campus career fair, received 2 phone interview and later on-site
Interview questions [1]
Question 1
Mostly hardware and architecture questions, phone interview asked about cache structure. Onsite interview are more focused on design a circuit to solve a problem.
I applied through college or university. The process took 2 days. I interviewed at NVIDIA
Interview
Contacted via my university, two basic phone interviews with members of the team. Each interview about an hour long, covers transistor related questions and basic operation of an oscilloscope
I applied through a recruiter. The process took 2 weeks. I interviewed at NVIDIA in Sep 2010
Interview
Went through a phone interview which consist of recruiting questions from HR. A second phone interview being technical which involves with how graphics z-buffering works.
After waiting for a few days, I got accepted to go to HQ for an in person interview.
Interview questions [1]
Question 1
-Explain CPU functions
-Explain the difference between a parallel CPU and GPU functions
-Transfer Array to the GPU using MatLabs. Create a 1000-by-1000 random matrix in MATLAB, and then transfer it to the GPU: