Key skills
Compiler technologiesC/C++ programmingPython programmingPerformance analysisDeep learning frameworksInterpersonal skillsProject managementMentoringPythonC++CAIDeep LearningPyTorchJAX
About this role
NVIDIA is a leading company in AI computing, known for its innovations in GPU technology. The role involves developing compiler optimization algorithms for deep learning networks and collaborating with various teams to enhance deep learning software performance.
Responsibilities:
- Analyzing deep learning networks and developing compiler optimization algorithms
- Collaborating with members of the deep learning software framework teams and the GPU architecture teams to accelerate the next generation of deep learning software
- Scope of these efforts includes defining public APIs, performance optimizations and analysis, crafting and implementing compiler techniques for AI workloads and future NVIDIA GPUs
Requirements:
- Bachelor's, Master's or Ph.D. in Computer Science, Computer Engineering, related field or equivalent experience
- 3+ years of relevant work or research experience in performance analysis and compiler optimizations
- Experience with compiler technologies (e.g., MLIR, LLVM, XLA, Triton, etc.)
- Excellent C/C++ and Python programming and software design skills, including debugging, performance analysis, and test design
- Ability to work independently, define project goals and scope, and lead your own development efforts
- Strong interpersonal skills are required along with the ability to work in a dynamic product-oriented team
- Proficient in CPU and/or GPU architecture
- CUDA or OpenCL programming experience
- Understanding of deep learning models, algorithms and frameworks, such as PyTorch, JAX
- GPU kernel authoring and performance analysis using tools such as Nsight Compute
- A track record of success in mentoring early-career engineers and interns is a bonus
- Track record on new hardware bring-up is a plus