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 -
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 seemed senior level engineers and asked basics of digital system design. They repeated the OA questions. I was also asked to solve a system verilog question. Cache and other architecture related questions were asked as well.
Interview questions [1]
Question 1
Q. What is cache coherence and MESI?
Q. What is cache eviction and caching algorithms
Q. Logical puzzle
Q. Wave-diagram from DIgital system design
The process began with a phone call from a recruiter to assess overall fit, confirm technical background, and discuss the role. This call may also cover basic behavioral questions to gauge interest and enthusiasm.