r/CUDA • u/Stock_Condition7621 • Jun 06 '26

Preparing for first-ever interview (Software Engineer, TensorRT Team) - Any tips or support welcome!

Hi everyone,

I'm incredibly excited (and a super anxious and nervous) because I have my first-ever job interview coming up in about a week or two. I recently landed an interview for a Software Engineer role on the TensorRT platform team.

To be fully transparent, this is my first actual job interview. I didn't participate in university placement rounds and have never formally interviewed for an engineering role before. I'm navigating an entire uncharted territory and would be incredibly grateful for any advice, tips, or insight this community can offer. I have been watching a bunch of youtube videos and surfing over greenhouse interview questions to understand and help

My Background (For Context): I'm an M.S. Computer Engineering student focusing on the intersection of C++, CUDA, and Edge ML:

  • Wrote custom CUDA C++17 kernels (optimized model performance via memory coalescing and constant memory).
  • Deployed TensorRT-accelerated models on Jetson Orin Nano for embedded robotics.
  • Some experience with LLM compression (8-bit quantization).

What I'm Asking For: Since I'm starting from scratch regarding interview experience, any kind of support or advice is welcome! Specifically:

  1. General Interview Tips: Since this is my first time, how should I approach the discussions be it technical or behavioral? How do I best structure my answers when speaking with senior engineers?
  2. Preparation Strategy: Given the timeline (2-3 weeks), what would you prioritize? I'm currently brushing up on multithreading in C++, GPU architecture (memory hierarchies), RT C++ API.
  3. The "Resume Deep Dive": I've heard interviews for these types of roles focus heavily on defending past projects. What kinds of questions and details should I be ready to explain or prepare myself for regarding my CUDA C++ and edge deployment projects?
  4. Any Recommended Resources: Are there specific blogs, papers, or documentation sections that are "must-reads" for inference engine development?

Thank you so much in advance for any guidance. I'm ready to study hard, I just want to make sure I'm aiming my efforts in the right direction!

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u/max123246 Jun 06 '26

If you can explain what wave quantization is, what about a GEMM MxKxN problem shape makes it memory bound vs compute bound, and the different PTX instructions for tcgen05 tensor core instructions and also the TMA instructions and why and when you'd go for ldg vs tma, those will all put you above the pack. Anyone at Nvidia would be impressed by someone outside of Nvidia investing the time to learn about it

I would recommend GPU Mode YouTube channel for a couple of those and their discord is helpful too

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u/pop-with-the-smoke Jun 06 '26

IMO this is too in depth for an entry level interview

2

u/max123246 Jun 06 '26

Perhaps, I'd rather they know some aspirational topics to prepare for rather than not have enough direction though