Nvidia Interview Questions

Review this list of 46 Nvidia interview questions and answers verified by hiring managers and candidates.
  • Nvidia logoAsked at Nvidia 
    +27

    "We had a huge launch on September 1st of this year where we completely redesigned our application from the grounds up and also migrated to a new platform (React.JS). This project took us 8 months and the launch was a huge deal for the team. Unfortunately the launch wasn't as smooth as we expected and despite doing multiple rounds of QA, some major issues cropped up in the core part of the app right after launch and our client was quite upset since it was disrupting their day-to-day workflow. "

    Aabid S. - "We had a huge launch on September 1st of this year where we completely redesigned our application from the grounds up and also migrated to a new platform (React.JS). This project took us 8 months and the launch was a huge deal for the team. Unfortunately the launch wasn't as smooth as we expected and despite doing multiple rounds of QA, some major issues cropped up in the core part of the app right after launch and our client was quite upset since it was disrupting their day-to-day workflow. "See full answer

    Technical Program Manager
    Behavioral
    +7 more
  • Nvidia logoAsked at Nvidia 

    "I started off with developing microservices for the game and then incorporating kafka to make it scalable"

    Kiran M. - "I started off with developing microservices for the game and then incorporating kafka to make it scalable"See full answer

    Software Engineer
    System Design
  • Nvidia logoAsked at Nvidia 
    Video answer for 'Tell me about a time when you worked on a project with a tight deadline.'
    +42

    "A clarifying question: Is this question asking about when I met a tight deadline in a project or how did I manage a project that had a tight deadline? The answer uploaded to this question is good, I would also add 'creating a critical path from overall project schedule and then making sure that none of the deliverables in the critical path are sacrificed in order to meet the tight deadline' as an action taken."

    Ushita S. - "A clarifying question: Is this question asking about when I met a tight deadline in a project or how did I manage a project that had a tight deadline? The answer uploaded to this question is good, I would also add 'creating a critical path from overall project schedule and then making sure that none of the deliverables in the critical path are sacrificed in order to meet the tight deadline' as an action taken."See full answer

    Product Manager
    Behavioral
    +5 more
  • Nvidia logoAsked at Nvidia 
    +28

    "Reversing a linked list is a very popular question. We have two approaches to reverse the linked list: Iterative approach and recursion approach. Iterative approach (JavaScript) function reverseLL(head){ if(head === null) return head; let prv = null; let next = null; let cur = head; while(cur){ next = cur.next; //backup cur.next = prv; prv = cur; cur = next; } head = prv; return head; } Recursion Approach (JS) function reverseLLByRecursion("

    Satyam S. - "Reversing a linked list is a very popular question. We have two approaches to reverse the linked list: Iterative approach and recursion approach. Iterative approach (JavaScript) function reverseLL(head){ if(head === null) return head; let prv = null; let next = null; let cur = head; while(cur){ next = cur.next; //backup cur.next = prv; prv = cur; cur = next; } head = prv; return head; } Recursion Approach (JS) function reverseLLByRecursion("See full answer

    Software Engineer
    Data Structures & Algorithms
    +4 more
  • Nvidia logoAsked at Nvidia 
    +53

    "I follow a variation of the RICE framework when prioritizing how I ship product features. I start by looking at: Reach: Because the customer segmentation across our product portfolio is so similar, I tend to hold a lot of weight on product features that will maximize our customer reach with a minimal LOE. Impact: After establishing which customer segments will benefit from the product feature, I determine the urgency and estimated impact on each customer segment based on customer i"

    Ashley C. - "I follow a variation of the RICE framework when prioritizing how I ship product features. I start by looking at: Reach: Because the customer segmentation across our product portfolio is so similar, I tend to hold a lot of weight on product features that will maximize our customer reach with a minimal LOE. Impact: After establishing which customer segments will benefit from the product feature, I determine the urgency and estimated impact on each customer segment based on customer i"See full answer

    Product Manager
    Behavioral
    +8 more
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  • "I like chatgpt for the following users Getting industry references are easy and time saving Getting recommendations is very easy Responses are accurate I use chatgpt to get feedback on content and identify gaps in my documentation or thought process I use chatgpt as a search engine and to get conscise situation based information. Chatgpt offers varierty of other tools in the explore version where similar users can create different content PRD template Chatgpt users 1."

    Shraddha D. - "I like chatgpt for the following users Getting industry references are easy and time saving Getting recommendations is very easy Responses are accurate I use chatgpt to get feedback on content and identify gaps in my documentation or thought process I use chatgpt as a search engine and to get conscise situation based information. Chatgpt offers varierty of other tools in the explore version where similar users can create different content PRD template Chatgpt users 1."See full answer

    Product Manager
    Product Design
    +3 more
  • Nvidia logoAsked at Nvidia 
    +15

    "We can use dictionary to store cache items so that our read / write operations will be O(1). Each time we read or update an existing record, we have to ensure the item is moved to the back of the cache. This will allow us to evict the first item in the cache whenever the cache is full and we need to add new records also making our eviction O(1) Instead of normal dictionary, we will use ordered dictionary to store cache items. This will allow us to efficiently move items to back of the cache a"

    Alfred O. - "We can use dictionary to store cache items so that our read / write operations will be O(1). Each time we read or update an existing record, we have to ensure the item is moved to the back of the cache. This will allow us to evict the first item in the cache whenever the cache is full and we need to add new records also making our eviction O(1) Instead of normal dictionary, we will use ordered dictionary to store cache items. This will allow us to efficiently move items to back of the cache a"See full answer

    Software Engineer
    Data Structures & Algorithms
    +5 more
  • Nvidia logoAsked at Nvidia 
    +5

    "As a PM i received a feedback from my program manager on my style of verbal communication. It is about me speaking faster when i wanted to get away with a topic that i wasn't confident (may be not backed up with data, or still in process of getting detailed insight of a problem etc.). Whereas when I'm confident I tend to speak slowly or more assertively that made people to follow easily. I welcomed that feedback so from then on when I'm not confident in a topic I became more assertive to let pe"

    Rajesh V. - "As a PM i received a feedback from my program manager on my style of verbal communication. It is about me speaking faster when i wanted to get away with a topic that i wasn't confident (may be not backed up with data, or still in process of getting detailed insight of a problem etc.). Whereas when I'm confident I tend to speak slowly or more assertively that made people to follow easily. I welcomed that feedback so from then on when I'm not confident in a topic I became more assertive to let pe"See full answer

    Product Manager
    Behavioral
    +6 more
  • Nvidia logoAsked at Nvidia 
    Video answer for 'Given an integer array nums and an integer k, return true if nums has a subarray of at least two elements whose sum is a multiple of k.'
    +9

    "Would be better to adjust resolution in the video player directly."

    Anonymous Prawn - "Would be better to adjust resolution in the video player directly."See full answer

    Software Engineer
    Data Structures & Algorithms
    +4 more
  • Nvidia logoAsked at Nvidia 

    "DNNs can learn hierarchical features, with each layer learning progressively more abstract features, and generalizes better. SNNs are better for simplier problems involving smaller datasets and if low latency is required."

    Louie Z. - "DNNs can learn hierarchical features, with each layer learning progressively more abstract features, and generalizes better. SNNs are better for simplier problems involving smaller datasets and if low latency is required."See full answer

    Software Engineer
    Concept
    +2 more
  • Nvidia logoAsked at Nvidia 
    Video answer for 'Merge Intervals'
    +33

    "const mergeIntervals = (intervals) => { const compare = (a, b) => { if(a[0] b[0]) return 1 else if(a[0] === b[0]) { return a[1] - b[1] } } let current = [] const result = [] const sorted = intervals.sort(compare) for(let i = 0; i = b[0]) current[1] = b[1] els"

    Kofi N. - "const mergeIntervals = (intervals) => { const compare = (a, b) => { if(a[0] b[0]) return 1 else if(a[0] === b[0]) { return a[1] - b[1] } } let current = [] const result = [] const sorted = intervals.sort(compare) for(let i = 0; i = b[0]) current[1] = b[1] els"See full answer

    Software Engineer
    Data Structures & Algorithms
    +6 more
  • Nvidia logoAsked at Nvidia 

    "Let me try to explain it with simple life analogy You're cooking dinner in the kitchen. Multithreading is when you've got a bunch of friends helping out. Each friend does a different job—like one chops veggies while another stirs a sauce. Everyone focuses on their task, and together, you all make the meal faster. In a computer, it's like different jobs happening all at once, making stuff happen quicker, just like having lots of friends helping makes dinner ready faster."

    Praveen D. - "Let me try to explain it with simple life analogy You're cooking dinner in the kitchen. Multithreading is when you've got a bunch of friends helping out. Each friend does a different job—like one chops veggies while another stirs a sauce. Everyone focuses on their task, and together, you all make the meal faster. In a computer, it's like different jobs happening all at once, making stuff happen quicker, just like having lots of friends helping makes dinner ready faster."See full answer

    Software Engineer
    Data Structures & Algorithms
    +1 more
  • Nvidia logoAsked at Nvidia 

    "performance issues and sudden spikes on input requests by scaling techniques and optimization."

    Srini K. - "performance issues and sudden spikes on input requests by scaling techniques and optimization."See full answer

    Product Manager
    Technical
    +5 more
  • Nvidia logoAsked at Nvidia 

    "Clarifying my assumptions first, i.e. "Technical contributions are not just writing or reviewing code". Answer : My contributions to any program I lead as a TPM are as follows : Inputs towards design, architecture review, mapping requirements to the proposed design, reviewing the implementation strategy w.r.t scalable solution, Writing core user-centric test scenarios, Validating proposed design vs implementation estimates vs initial planning. etc... Example : Situation: We are a"

    DM - "Clarifying my assumptions first, i.e. "Technical contributions are not just writing or reviewing code". Answer : My contributions to any program I lead as a TPM are as follows : Inputs towards design, architecture review, mapping requirements to the proposed design, reviewing the implementation strategy w.r.t scalable solution, Writing core user-centric test scenarios, Validating proposed design vs implementation estimates vs initial planning. etc... Example : Situation: We are a"See full answer

    Technical Program Manager
    Technical
    +2 more
  • Nvidia logoAsked at Nvidia 
    Video answer for 'Write functions to serialize and deserialize a list of strings.'
    +4

    "function serialize(list) { for (let i=0; i 0xFFFF) { throw new Exception(String ${list[i]} is too long!); } const prefix = String.fromCharCode(length); list[i] = ${prefix}${list[i]}; console.log(list[i]) } return list.join(''); } function deserialize(s) { let i=0; const length = s.length; const output = []; while (i < length) { "

    Tiago R. - "function serialize(list) { for (let i=0; i 0xFFFF) { throw new Exception(String ${list[i]} is too long!); } const prefix = String.fromCharCode(length); list[i] = ${prefix}${list[i]}; console.log(list[i]) } return list.join(''); } function deserialize(s) { let i=0; const length = s.length; const output = []; while (i < length) { "See full answer

    Software Engineer
    Coding
    +1 more
  • " Project Overview: Real-Time Risk Management System Objective The goal was to develop a real-time risk management system capable of processing and analyzing large volumes of trading data to provide near-instantaneous risk assessments. This system was crucial for enabling traders to make informed decisions while managing their exposure to various market risks in real-time. Complexity Factors 1. \\Data Volume and Velocity\\ \\High Throughput:\\ The system needed to ha"

    Scott S. - " Project Overview: Real-Time Risk Management System Objective The goal was to develop a real-time risk management system capable of processing and analyzing large volumes of trading data to provide near-instantaneous risk assessments. This system was crucial for enabling traders to make informed decisions while managing their exposure to various market risks in real-time. Complexity Factors 1. \\Data Volume and Velocity\\ \\High Throughput:\\ The system needed to ha"See full answer

    Technical Program Manager
    Behavioral
    +1 more
  • Nvidia logoAsked at Nvidia 
    Software Engineer
    Data Structures & Algorithms
    +4 more
  • Nvidia logoAsked at Nvidia 
    Software Engineer
    Data Structures & Algorithms
    +4 more
  • Nvidia logoAsked at Nvidia 
    Video answer for 'Given an nxn grid of 1s and 0s, return the number of islands in the input.'
    +9

    " from typing import List def getnumberof_islands(binaryMatrix: List[List[int]]) -> int: if not binaryMatrix: return 0 rows = len(binaryMatrix) cols = len(binaryMatrix[0]) islands = 0 for r in range(rows): for c in range(cols): if binaryMatrixr == 1: islands += 1 dfs(binaryMatrix, r, c) return islands def dfs(grid, r, c): if ( r = len(grid) "

    Rick E. - " from typing import List def getnumberof_islands(binaryMatrix: List[List[int]]) -> int: if not binaryMatrix: return 0 rows = len(binaryMatrix) cols = len(binaryMatrix[0]) islands = 0 for r in range(rows): for c in range(cols): if binaryMatrixr == 1: islands += 1 dfs(binaryMatrix, r, c) return islands def dfs(grid, r, c): if ( r = len(grid) "See full answer

    Software Engineer
    Data Structures & Algorithms
    +4 more
  • Nvidia logoAsked at Nvidia 

    "Over-fitting of a model occurs when model fails to generalize to any new data and has high variance withing training data whereas in under fitting model isn't able to uncover the underlying pattern in the training data and high bias. Tree based model like decision tree and random forest are likely to overfit whereas linear models like linear regression and logistic regression tends to under fit. There are many reasons why a Random forest can overfits easily 1. Model has grown to its full depth a"

    Jyoti V. - "Over-fitting of a model occurs when model fails to generalize to any new data and has high variance withing training data whereas in under fitting model isn't able to uncover the underlying pattern in the training data and high bias. Tree based model like decision tree and random forest are likely to overfit whereas linear models like linear regression and logistic regression tends to under fit. There are many reasons why a Random forest can overfits easily 1. Model has grown to its full depth a"See full answer

    Machine Learning Engineer
    Concept
    +2 more
Showing 1-20 of 46