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 -
Some leetcode and questions about resnet and research experience. I worked on heart rate and oxygen saturation detection and was interviewed by deep learning and automotive teams. The interviewers are solid in technical background.
Interview questions [1]
Question 1
Explain your research paper on computer vision algorithm for heart rate detection.
I applied through college or university. The process took 5 weeks. I interviewed at NVIDIA in Oct 2025
Interview
The interview was intensive. I got 9 sessions of interviews separated into 4 rounds. The interview covers computer architecture knowledge, power related VLSI design questions. It was more important to give them the "idea" than the "right answer".
I applied through college or university. I interviewed at NVIDIA
Interview
Eligibility criteria to sit was more than 7.8 cgpa and then online assessment was the first step but couldn't clear the step one as all the Nits IIITs and IITs sit together.