Senior AI Compute Engineer - GPU & Parallel Optimizations

NVIDIA

Zürich

Vor Ort

CHF 140.000 - 210.000

Vollzeit

Vor 3 Tagen
Sei unter den ersten Bewerbenden
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Zusammenfassung

NVIDIA is seeking a Senior Developer Technology Engineer in Artificial Intelligence to research and develop techniques that accelerate AI workloads on modern CPUs and GPUs. You will work with researchers and developers across NVIDIA to optimize AI and HPC algorithms and publish findings to the community.

The role emphasizes collaboration with hardware, software, and tooling teams to influence future architectures and programming models.

Qualifikationen

  • Advanced degree in Computer Science, Computer Engineering, or related computationally focused science degree (or equivalent experience).
  • 8+ years of relevant experience in software development or research work.
  • Programming fluency in C/C++ with deep knowledge of algorithms.
  • Background in parallel programming: CUDA, OpenACC, OpenMP, MPI, pthreads.
  • Hands-on experience doing low-level performance optimizations.
  • In-depth expertise with CPU and GPU architecture fundamentals.
  • Effective communication and organization skills, with good time management.

Aufgaben

  • Research and develop techniques to GPU-accelerate workloads in AI domains.
  • Collaborate with experts to analyze and optimize complex AI/HPC algorithms.
  • Publish/disseminate optimization techniques in blogs or conferences.
  • Influence design of next-gen hardware, software, and programming models.

Kenntnisse

Parallel programming
Performance optimization
CPU/GPU architecture
Strong communication

Ausbildung

Advanced degree

Tools

CUDA
OpenACC
OpenMP
MPI
pthreads

Jobbeschreibung

NVIDIA is seeking a Senior Developer Technology Engineer in Artificial Intelligence to research and develop techniques that accelerate AI workloads on modern CPUs and GPUs. You will work with researchers and developers across NVIDIA to optimize AI and HPC algorithms and publish findings to the community.

The role emphasizes collaboration with hardware, software, and tooling teams to influence future architectures and programming models.

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