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).
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almost 2 hours, very nice interviewers, asked 1 logical thinking question and 1 buffering question.
Second interview was held in a different office, almost 2 hours, a lot of personal questions
HR contacted me and set up the interview. 60 minutes interview each. The first interview was easier, the second interview was comparatiely harder. Questions covered topics from Computer Architecture, FIFO depth, RTL design, encoders , basic C codes and Systemverilog.
Interview questions [1]
Question 1
Computer Architecture, FIFO depth calculation, how to design Power, Performance, or Area-efficient RTLs, also some questions regarding pipeline hazards.
I applied through a recruiter. The process took 2 months. I interviewed at NVIDIA (Santa Clara, CA) in Oct 2025
Interview
initial interview was hour video conference with a group style panel
later went on site to do 1-on-1 interviews with team, for two hours.
they asked a variety of tech questions and scenarios. some of the questions felt a bit contrived, but perhaps they were actual scenarios
Interview questions [1]
Question 1
If a system partial boots and passes through MBR phase, but gets stuck at the kernel loader, what could be possible problems and how would they be resolved?