Senior AI Performance Engineer - GPU-Accelerated DL & LLMs

NVIDIA Corporation; Santa Clara (CA); Hybrid; USD 184.000 - 357.000; Vollzeit

Benefits dieser Stelle

Equity

Benefits

Hybrid work model

Zusammenfassung

NVIDIA Corporation is seeking a Senior AI Developer Technology Engineer to push the performance frontier of generative AI training and inference on NVIDIA systems. You will work with developers worldwide to accelerate workloads, optimize algorithms, and contribute to core libraries and frameworks.

Ideal candidates bring MS-level education in CS/related fields, 8+ years of software performance experience, and deep expertise in C/C++ with a strong foundation in CPU/GPU architectures.

Qualifikationen

• MS in Computer Science, Computer Engineering, or related field; equivalent experience.
• 8+ years of relevant work or research in software engineering and performance tuning.
• Fluency in C/C++ with emphasis on algorithms and software development.
• Background in accelerated computing with parallel programming and optimization.

Aufgaben

• Develop GPU-accelerated techniques for generative AI workloads including LLMs, diffusion, and multimodal models.
• Collaborate with developers to optimize AI training and inference on NVIDIA platforms.
• Build and optimize algorithms; contribute to training/inference frameworks and libraries.
• Partner with industry and academic experts to analyze and optimize AI algorithms on CPU/GPU architectures.
• Guide design of hardware, system software, libraries, and programming models through cross-team collaboration.
• Publish breakthroughs via developer blogs and present at conferences.

Kenntnisse

C/C++

Parallel programming

Performance tuning

Low-level optimization

CPU architecture

GPU architecture

Communication

Problem solving

Ausbildung

MS in CS

Jobbeschreibung

NVIDIA Corporation is seeking a Senior AI Developer Technology Engineer to push the performance frontier of generative AI training and inference on NVIDIA systems. You will work with developers worldwide to accelerate workloads, optimize algorithms, and contribute to core libraries and frameworks.

Ideal candidates bring MS-level education in CS/related fields, 8+ years of software performance experience, and deep expertise in C/C++ with a strong foundation in CPU/GPU architectures.