Nvidia GPU Kernel Compiler Engineer AI Inference 

United States, Texas 

86673648

What you will be doing:

• Analyze state-of-the-art AI models, identifying key performance bottlenecks and opportunities at the kernel level.

• Develop, optimize, and evaluate both hand-tuned and compiler-generated kernels for inference workloads, balancing speed and flexibility.

• Design and build high-level DSLs and innovative compiler infrastructure to increase kernel developer productivity while achieving near peak performance.

• Collaborate with model AI inference and compiler teams to iterate on kernel fusion, auto tuning, and sophisticated GPU programming techniques.

• Benchmark performance across real workloads, diagnose root causes, and rapidly deploy optimizations that maximize hardware utilization on NVIDIA platforms.

What we need to see:

• Bachelor’s, master’s or PhD degree in Computer Science, Computer Engineering or related field, or equivalent experience.

• At least 3+ years Strong C++ and/or Python programming skills for system and performance engineering.

• Understanding of GPU architecture and proficiency in CUDA programming.

• Intellectual curiosity and interest to solve exciting problems and deliver practical results in production environments.

Ways to stand out from the crowd:

• Experience designing, developing and optimizing high-efficiency GPU kernels for modern AI workloads.

• Experience building compilers, domain-specific languages, or automatic optimization systems

• Familiarity with popular compiler, GPU programming and AI frameworks such as MLIR, LLVM, PyTorch, XLA, Triton or Cutlass.

• Experience with AI/ML inference workloads and model performance analysis.

• Strong communication skills and ability to collaborate in a cross-team environment.