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Getting a job at Nvidia as a software engineer

Master CUDA, system architecture, and deep learning for Nvidia engineering roles.

8 lessons
3 weeks
800 XP
Your progress0 / 800 XP
Click a lesson to start learning!
Lessons
1
Mapping the Nvidia Technical Interview Landscape
Navigate the specific domain requirements for hardware-software co-design and systems roles.
Quick winTheoryMilestone
+50 XP
~5 min
2
Advanced CUDA Memory Hierarchy Optimization
Implement shared memory tiling and coalesced access patterns for maximum throughput.
AdvancedPractice
+75 XP
~8 min
3
Low-Level Systems and Kernel Programming
Master synchronization primitives, atomic operations, and custom memory allocators for GPUs.
AdvancedMilestone
+75 XP
~10 min
4
Optimizing Deep Learning Inference with TensorRT
Quantize models and utilize FP16/INT8 precision for high-performance deployment.
ProjectIntermediate
+100 XP
~12 min
5
High-Performance Distributed Systems and NCCL
Scale multi-GPU workloads using Nvidia Collective Communications Library for clusters.
AdvancedTheoryMilestone
+100 XP
~14 min
6
Architecting Scalable Driver and API Layers
Design efficient software abstractions that interface directly with hardware registers.
AdvancedPracticeMilestone
+125 XP
~16 min
7
Performance Profiling with Nsight Systems
Identify bottlenecks in complex pipelines using Nsight Systems and Compute tools.
AdvancedPractice
+125 XP
~18 min
8
Capstone: End-to-End GPU Accelerated Pipeline
Build and optimize a complete high-performance system for the Nvidia panel.
ProjectMilestoneMilestone
+150 XP
~20 min

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