Software Engineer, Cuda-q Libraries

NVIDIA NVIDIA · Semiconductors · CA +3 · Remote

Software engineer to build the CUDA-Q platform for programming hybrid quantum-classical multi-processor systems, focusing on developing analysis libraries, implementing AI decoding algorithms, and building AI training infrastructure for QEC.

What you'd actually do

  1. Develop analysis libraries and tools to characterize QEC codes and parameters for a variety of quantum applications
  2. Identifying, implementing, and productizing AI and algorithmic real-time decoding algorithms in collaboration with NVIDIA's Applied Research team
  3. Contributing to the development of CUDA Quantum libraries by building AI training infrastructure for the CUDA-Q Quantum Error Correction (QEC) library
  4. Developing real-time hardware and software interfaces for the heterogenous quantum/classical computing enabled by CUDA Quantum
  5. Developing and improving CI/CD pipelines for new and existing products to ensure high product quality

Skills

Required

  • C/C++
  • algorithm analysis and implementation on heterogenous systems (CPUs, GPUs, FPGAs)
  • software engineering
  • high-performance algorithm implementation

Nice to have

  • quantum computing hardware and control systems
  • Quantum Error Correction
  • implementing decoding algorithms
  • software optimizations of real-time systems
  • improving extensibility
  • CI/CD pipelines in GitHub, GitLab, and Jenkins

What the JD emphasized

  • C/C++ proficiency is required
  • real-time systems
  • GPU programming
  • parallel and distributed programming
  • AI training infrastructure

Other signals

  • AI and algorithmic real-time decoding algorithms
  • AI training infrastructure for the CUDA-Q Quantum Error Correction (QEC) library