Since NVIDIA works extensively on robotics and accelerated computing, the interviewer focused on how I would test systems where AI models, hardware and software interact with each other.

Physical AI & Robotics

What is Physical AI, and how is it different from traditional generative AI?

What are the challenges of deploying AI models on robots?

How would you test an autonomous robot operating in an unpredictable environment?

How would you approach testing a robot's perception system?

What happens when a robot receives incorrect or inconsistent sensor data?

How would you test edge cases in a robotic system?

Hardware & GPU Computing

How does a GPU execute parallel workloads?

What is the difference between CPU and GPU execution?

How would you test an AI model running on an NVIDIA GPU?

What factors can cause performance degradation during GPU inference?

How would you identify whether a failure originates from hardware, drivers or software?

What is the role of CUDA in GPU-accelerated computing?

QA & System Testing

How would you design a test strategy for an end-to-end robotic system?

How would you distinguish between a hardware failure and a software bug?

How would you automate testing for systems involving physical hardware?

What is hardware-in-the-loop (HIL) testing?