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. I interviewed at NVIDIA
Interview
First,we talked about my personal project and previous experiences.
Second, we have several questions about Python Basics.
About coding part: the classic DFS question about island, which can be found in Leetcode
Interview questions [1]
Question 1
coding part: the classic DFS question about island, which can be found in Leetcode
I had 3 rounds. The first was with a member of the team, where I explained my research and elaborated on technical details to demonstrate my understanding of comp bio/ML. The second round was a coding round where they asked me to code k-means from scratch. They also asked me technical ML questions. Third round was with the director, and it focused a lot on biological interpretation of ML concepts in bionformatic methods.
Interview questions [1]
Question 1
Which ensemble learning method, random forest or gradient boosting, has more bias and which one has more variance?
Two technicals interviews.
First one was In zoom, the second one was 2 on 1 with team member and the team manager.
Both of the interviews were in C.
Got a rejection email.