NVIDIA's VLSI Productivity and Infrastructure team needs to build tools and platforms that enhance the productivity of chip design engineers by addressing challenges across databases, web applications, build automation, machine learning, and infrastructure.
Requirements
- 5+ years developing large-scale software applications in at least two programming languages
- 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 using Perl and Python
- Understand filesystems, job-scheduling, and JSON-RPC
Responsibilities
- 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
Other
- B.S. CS/EE (or equivalent experience)
- Highly self-sufficient in the face of ambiguity, with strong reasoning and problem-solving skills
- Rapid comprehension of existing codebases to identify and implement high-leverage changes effectively
- creative and autonomous engineer with a real passion for technology
- Applications for this job will be accepted at least until November 22, 2025.
