Eda Workflow Optimization Engineer

NVIDIA NVIDIA · Semiconductors · Santa Clara, CA +3

NVIDIA is seeking an EDA Workflow Optimization Engineer to partner with engineering teams worldwide to understand and improve chip design workflows. The role involves investigating complex problems, building metrics, and enhancing scalable systems and tools to enable the next generation of chips. This is an engineering role focused on optimizing existing workflows and tools within the chip design process, not directly building AI models or systems.

What you'd actually do

  1. Work in a diverse team performing fast paced investigations to empower our engineers to develop at the speed of light.
  2. Participate in the full life-cycle of tool development, test, and deployment.
  3. Work closely with other team members and chip engineers to understand and optimize how workflows use the compute and storage environments.
  4. Build metrics that are reliable and easy to use by hundreds of engineers around the world.
  5. Continuously improve our chip development process.

Skills

Required

  • investigating and debugging complex, multi-discipline problems in a UNIX engineering environment
  • architectural decisions in technologies (storage, networking, compute)
  • ASIC, VLSI, CAD/EDA or mixed signal design workflow environments
  • EDA tools
  • UNIX Systems programming and automation using Python and/or Shell
  • Authoritative level usage of UNIX and UNIX utilities
  • data analysis principles
  • Flexibility/adaptability working in a dynamic environment with changing requirements
  • BS in Computer Science or equivalent experience

Nice to have

  • Experience with job schedulers (in particular IBM Spectrum LSF and/or SLURM)
  • Hands-on experience running GPU-based workloads in a batch computing environment and a deep understanding of distributed system principles
  • Strong programming and debugging skills with C/C++, Python, and Perl on UNIX
  • A passion for improving engineering productivity and efficiency via data-driven philosophy
  • MS (preferred)

What the JD emphasized

  • complex, multi-discipline problems
  • architectural decisions
  • ASIC, VLSI, CAD/EDA or mixed signal design workflow environments
  • EDA tools
  • UNIX Systems programming and automation using Python and/or Shell
  • Authoritative level usage of UNIX and UNIX utilities
  • data analysis principles
  • dynamic environment with changing requirements