Nvidia-posted about 1 month ago
Full-time • Mid Level
Santa Clara, CA
5,001-10,000 employees
Computer and Electronic Product Manufacturing

We are looking for inquisitive and driven full-time software engineers with a strong interest in building high-quality, long-lasting systems. The VLSI Productivity and Infrastructure team supports hundreds of chip design engineers by building tools and platforms that supercharge their everyday work. From databases to web applications, build automation to machine learning, and on-prem infrastructure to cloud workloads, our team handles it all. Want to know how NVIDIA stays at the top of the pack? Come join us to find out!

  • Design, development, and delivery of core components of our next-generation VLSI productivity platforms.
  • Design, build, deploy, and improve highly scalable systems
  • Translate high-level requirements into actionable plans/deliverables
  • Leverage LLMs to accelerate (not replace) your contribution while taking ownership of your output
  • Convert legacy codebases into modern powerhouses infused with industry best-practices
  • Collaborate with engineering teams to identify and alleviate bottlenecks in their daily tasks
  • B.S. CS/EE (or equivalent experience)
  • 5+ years developing large-scale software applications in Go and Python
  • Solid computer science fundamentals in algorithms/data structures/complexity analyses
  • Understand processes, synchronization, locks, concurrency, and load-balancing
  • Excellent grasp of distributed systems and compute abstractions
  • Experience building custom solutions around open-source products and libraries to solve feature-gaps fast
  • 5+ years in an enterprise engineering environment, shipping at scale
  • Experience in partitioning and optimizing complex interconnected systems
  • Understand filesystems, job-scheduling, and inter-process signaling
  • Highly self-sufficient in the face of ambiguity, with strong reasoning and problem-solving skills
  • Rapid comprehension of existing codebases (in any language) to implement high-leverage changes effectively
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