Interview Experience @ NVIDIA: Senior System Software Engineer [2024]

NVIDIA, a pioneer in AI and high-performance computing, has always been a company I admired. Recently, I had the chance to interview for the Senior System Software Engineer position, and here’s my detailed experience.

Getting Started: Referral and Screening

The journey began with a referral for the role and an invitation to participate in a screening round. This 45-minute session tested my basic problem-solving and programming skills.

• Coding Question: A LeetCode easy-to-medium problem involving hashmaps.
• Design Question: Implementing a singleton class in C++.

Clearing this round was essential to proceed to the next stage, where I faced five technical rounds, all scheduled on the same day.

The Technical Marathon: Five Rounds in One Day

Round 1: Algorithms Round (60 mins)

This session tested my problem-solving skills. I was presented with a medium-level LeetCode problem, which I solved while discussing my approach and analyzing the time and space complexities.

Round 2: C/C++/Python Round (60 mins)

This round began with a simple C++ problem — calculating the average of a set of numbers. From there, the discussion escalated to:

• Optimizing the solution for streaming cases.
• Advanced concepts like vectorization, SIMD, and set-associative caching in memory systems.

Round 3: AI/ML Round (60 mins)

This round was focused on my knowledge of transformers and related concepts. A key highlight of the discussion was proving that Large Language Models (LLMs) are memory-intensive rather than purely compute-intensive.

The conversation extended into optimization strategies for memory usage and eventually delved into set-associative caching and its relevance in managing memory in AI applications.

Round 4: Coding Skills Round (60 mins)

This round featured another dynamic programming (DP) problem from LeetCode’s medium category. The interviewer assessed my solution and my ability to communicate my thought process and write efficient, clean code.

Round 5: Problem Solving + ML Round (60 mins)

The final technical round was resume-focused. The interviewer asked about my projects :

• Challenges I encountered during implementation and how I addressed them.
• Practical optimization techniques for machine learning models.

Job Location and HR Discussion

The job location for this position was Pune, which wasn’t my top preference. However, given NVIDIA’s reputation and the alignment of this role with my expertise, I expressed my willingness to relocate.

Key Takeaways

1. Competitive Programming: The practice I was doing for Google helped me a lot to tackle CP rounds of Nvidia
2. AI/ML Depth: Be prepared to discuss transformers, memory optimization, and other advanced topics in AI and ML.
3. Multilingual Proficiency: Proficiency in C++, Python, and algorithmic problem-solving is critical.
4. System-Level Knowledge: Expect discussions on computer architecture and other system-level concepts.
5. Flexibility Pays Off: Sometimes, job locations may not align with your preferences, but being open to opportunities can lead to excellent outcomes.

Final Thoughts

The NVIDIA interview process was intense but immensely rewarding. It challenged me to demonstrate my technical expertise and problem-solving skills across diverse domains. If preparing for an NVIDIA interview, strengthen your AI/ML concepts, coding skills, and system-level understanding.

Feel free to contact me on LinkedIn for any specific queries about the process.

“Every challenge is an opportunity to grow and excel. Keep pushing your boundaries!”