nvidia
1 interview experience from candidates.
NVIDIA | Deep Learning Algorithm Engineer (Junior/New Grad) | Screen | Phone Screen
Deep Learning Algorithm Engineer
30 minute HM screen round. Below were the questions. 1. if you have a GPU at 100% util given a batch size and some throughput/latency numbers, how are these affected when you increase batch size further 2. How to identif...
NVIDIA | Deep Learning Algorithm Engineer (Junior/New Grad) | Coding | Phone Screen
Deep Learning Algorithm Engineer
1. What are important transformer layers, and what is time complexity of each of them in terms of lenght of seuqeunce and batch size. (The interviewer basically wanted to know that i understand that Attention is the bott...
NVIDIA | Deep Learning Algorithm Engineer (Junior/New Grad) | Technical | Phone Screen
Deep Learning Algorithm Engineer
1. Explain activation checkpointing 2. Between tensor parallel and data parallel, which would you use for latency sensitive applications 3. given an ML model in the wild, what steps would you take to profile it and optim...
Nvidia | Full stack | Coding | Onsite
Full stack
Design rate limiter. Input is an array of domain names. We need to output whether or not this domain is allowed. Input: ["abc.com","xyz.com","abc.com"] Conditions 1. Allow 2 requests per domain within 5second interval 2....
Nvidia | System Software Engineer, Distributed Systems | Coding | Phone Screen
System Software Engineer, Distributed Systems
find the number of good subsequence all element in subsequence are unique min(sub)=a, max(sub)=b, all element between [a,b] should be present in subsequence return numbers of all good subsquences example: 13 11 4 12 5 4...