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NVIDIA interview notes, page 6 of 17

FAANG / Big Tech

Most of these NVIDIA write-ups come from Software Engineers (137), then Product Managers (15) and Data Scientists (10). The most reported rounds are the technical phone screen (106), the system design round (28), the hiring manager screen (13) and the product sense round (13).

166 interview notes · updated Aug 2026

NVIDIA·Software Engineer·Technical Phone Screen

May 2026
Technical screen at NVIDIA for a software engineer role, focused almost entirely on deep ML inference optimization. Three meaty questions back to back, no warmup, no behavioral fluff. Whoever designed this loop clearly wanted to see if you actually know this stuff or just read the docs once.
  • Explain PyTorch Dynamo and how it fits into inference acceleration, including how it captures and compiles computation graphs and how it connects to backends like TorchInductor and TensorRT.
  • Walk through multiple techniques for speeding up model inference, covering things like parallelism strategies, batching, operator fusion, quantization, kernel autotuning, CUDA Graphs, overlapping compute with data transfer, sparsity, caching, and compiler-level optimizations.
  • How would you design a rigorous and fair inference benchmark? Cover what metrics you'd track, how you'd set up the test environment, what baselines you'd use, and how you'd present the results.

“This one tripped me up a bit because I kept conflating what Dynamo does versus what the backend does.”

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NVIDIA·Software Engineer·Technical Phone Screen

May 2026
NVIDIA software engineer interview with a tricky DP problem involving subarray selection under multiple constraints. Not a typical easy/medium style question, more like something you'd see in a competitive programming contest.
  • Given an integer array and three limits x, y, z representing the maximum number of subarrays of length 1, 2, and 3 you can pick, select non-overlapping contiguous subarrays to maximize the total sum without exceeding the per-length limits. Return the maximum sum.

“I stared at this for a bit before realizing it's a 4D DP problem.”

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NVIDIA·Product Manager·Hiring Manager Screen

May 2026
Interviewed for a PM role at Nvidia, just one question about stakeholder management from what I can tell. Short and a bit underwhelming but it still made me think.
  • How did you handle stakeholder management on your past projects?

“Pretty broad question and I kind of rambled.”

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NVIDIA·Software Engineer·Technical Phone Screen

May 2026
Interviewed for a SWE role at Nvidia, pretty short technical screen. Just one coding question, nothing too wild, but I fumbled around more than I should have for something this basic.
  • Write a function that checks whether a given string contains a specific substring.

“Felt almost too easy and that made me second-guess myself.”

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NVIDIA·Software Engineer·Technical Phone Screen

May 2026
NVIDIA software engineer interview with a classic bracket matching problem. Nothing too wild, but the stack-based approach is one of those things you either have locked in or you fumble under pressure.
  • Given a string containing only bracket characters, write a function to determine whether the brackets are all properly matched and closed in the correct order.

“Pretty standard stack problem.”

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NVIDIA·Software Engineer·Technical Phone Screen

May 2026
Interviewed for a SWE role at Nvidia and got hit with an OS fundamentals question pretty early on. Nothing crazy but it made me realize I'd been fuzzy on some of these distinctions for years.
  • What is the difference between multiprogramming, time-sharing, and multiprocessing?

“I knew the rough idea but fumbled the exact distinction between multiprogramming and time-sharing.”

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NVIDIA·Software Engineer·Technical Phone Screen

May 2026
Phone screen for a software engineering role at NVIDIA, Linux-oriented. Two coding problems and apparently a C code review, though the C snippet itself wasn't shared so I can't say much about that part. Pretty standard technical screen but the key-value store design had some nuance worth thinking through.
  • Given an n x n matrix, write a function to return its transpose (swap rows and columns so that result[i][j] equals the original matrix[j][i]).
  • Design an object-oriented key-value store that supports set(key, value), get(key), and a setAll(value) operation that updates every existing key at once. Walk through the time complexity of each operation.

“Fairly mechanical once you see it.”

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NVIDIA·Software Engineer·Technical Phone Screen

May 2026
NVIDIA coding interview with a classic grouping problem. Nothing too wild but it's the kind of question where your first instinct can lead you down a slow path if you're not careful.
  • Given an array of strings, group all anagrams together. Two strings are anagrams if they share the same characters at the same frequencies. Order of the groups doesn't matter.

“My first move was sorting each string and using that as a hash map key, which works fine.”

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NVIDIA·Software Engineer·Technical Phone Screen

May 2026
NVIDIA software engineer interview that was heavy on CS fundamentals. Nothing too wild but they really wanted you to know your data structures cold, like not just the buzzwords but the actual mechanics underneath.
  • What are the best, average, and worst case time complexities for common sorting algorithms like bubble sort, insertion sort, selection sort, merge sort, quicksort, and heap sort?
  • Compare arrays and linked lists. What are the time complexities for element access, inserting at the head, and inserting in the middle?
  • Walk through the full process of inserting an element at the head of a dynamic array, including what happens internally when the array has to resize.
  • What is a hash table and how does it work under the hood? How are collisions handled?
  • What is the difference between a hash table and a hash map, both conceptually and in terms of how languages like Java implement them?
  • What is the difference between a binary tree and a binary search tree?

“I knew most of these but blanked on insertion sort's best case being O(n) for nearly sorted input.”

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NVIDIA·Software Engineer·Technical Phone Screen

May 2026
NVIDIA technical screen for a software engineer role, heavy on parallel computing theory. One question, but it had a lot of moving parts and felt more like a mini lecture than a typical interview.
  • State Amdahl's Law and derive the theoretical maximum speedup S(N) for N processors given a parallelizable fraction p of execution time. Then walk through: the asymptotic limit as N grows unbounded, what this means for GPU/parallel workload design, how it compares to Gustafson's Law, and a numeric example using p=0.95 at N=10 and N=1000.

“This was a lot to unpack in one question.”

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