Nvidia-posted 3 months ago
$184,000 - $287,500/Yr
Full-time • Mid Level
Santa Clara, CA
Computer and Electronic Product Manufacturing

We're looking for AI-accelerated programmers to help us engineer new paradigms in productivity infrastructure and platforms. If you feel one with the machine when you vibe-code while retaining a deep understanding of the fundamentals of programming, you can harness the power of AI Agents. The VLSI Productivity and Infrastructure team supports hundreds of chip design engineers by building tools and platforms that supercharge their everyday work. From workflow automation to machine learning, and ETL pipelines to web applications, our team handles it all. We are modernizing the entire silicon engineering stack, and no prior experience in chip design is expected for this role. If you have a strong interest in building high-quality, long-lasting systems, you'll fit right in!

  • Design, develop and deliver core components of our next-generation engineer productivity platforms.
  • Envision, build, deploy and improve highly scalable systems at the speed of thought.
  • Disambiguate high-level requirements into actionable Agentic AI tasks with clear vetting and ownership of output.
  • Jump between microservices and monoliths, on-prem and cloud-compute as needed to build efficient products.
  • Convert legacy codebases into modern powerhouses with parallelized AI migration.
  • Collaborate with engineering teams to identify and alleviate bottlenecks in their daily tasks.
  • Be adept and flexible to changing priorities and updating your codebases as business needs evolve.
  • Proficiency in thought-to-code and rapid understanding of existing or AI-generated code to debug and identify pathways to improve performance, resilience and observability.
  • M.S. in EE/CS (or equivalent experience).
  • Minimum 5 years developing large-scale software applications in an enterprise engineering environment using Python.
  • Internalized computer science fundamentals in algorithms/data structures/complexity analyses.
  • Rich history of wrangling LLMs (GPT 4o through Claude Opus 4.x) to ship real software.
  • Deep, demonstrable intuition of the capabilities and pitfalls of LLM code generation ('vibe coding').
  • Track record of shipping and supporting AI-generated code into enterprise engineering applications.
  • Core system-engineering skills including the ability to visualize strongly-coupled systems from architecture down to OS and compute.
  • Solid fundamentals of UNIX internals, filesystems, job-scheduling, processes, synchronization, and locks.
  • Experience with Perforce, NFS, LSF and running services on managed infrastructure without root/sudo.
  • Experience building maintainable software using off-the-shelf tools and open-source libraries to solve feature gaps quickly.
  • You've handled your own deployment and infrastructure on a cloud provider and on bare-metal servers.
  • Rapid problem decomposition and clear communication when delegating work to AI Agents.
  • Competitive salaries
  • Generous benefits package
  • Equity eligibility
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