Software R&D Engineer, VLSI Physical Design - New College Grad 2026
NVIDIAJob Title
Software R&D Engineer, VLSI Physical Design — New College Graduate (2026)
Role Summary
Join NVIDIA's VLSI physical design software team to develop high-performance EDA tools that improve chip frequency and power for advanced AI hardware. The team combines parallel computing, machine learning, and specialized algorithms to create internal optimization engines used directly by design teams.
The role focuses on research and product-quality implementation of physical design algorithms and their integration into deployment flows.
Experience Level
Entry-level — new college graduate (2026). Appropriate for early-career engineers; equivalent practical experience considered.
Responsibilities
Deliver research and production-quality software that advances physical design optimization across the implementation flow.
- Invent and implement optimization engines that fuse multiple physical-design steps (e.g., co-optimization of legalization and sizing).
- Design and improve C++ algorithms for gate-level sizing, buffering, useful clock skew, cell legalization, power minimization, ECO routing, and incremental parasitic extraction.
- Profile and optimize software for performance, memory, concurrency, and I/O efficiency.
- Collaborate with silicon design teams to deploy tools and validate improvements in PPA (performance, power, area).
- Own the development lifecycle from discovery and prototyping to production delivery and maintenance.
Requirements
Key technical skills and experience required or strongly preferred.
- Must-have: Experience with VLSI algorithms development in C++.
- Understanding of VLSI timing optimization concepts: cell libraries, interconnect models, crosstalk, glitches, IR drop, timing constraints, corners, and congestion.
- Familiarity with physical-design implementation tools and flows (examples: ICC2/Innovus, PrimeTime/Tempus, StarRC) and scripting in Perl, Tcl, or Python.
- Nice-to-have: Modern C++ (C++14+) features, concurrency and lambda usage.
- Experience in high-performance software design: multithreading, distributed computing, efficient memory and I/O usage.
- Knowledge of how multiple physical-design steps interact and strategies to fuse them for better PPA.
- Experience applying machine learning (reinforcement learning, GNNs) to physical design problems.
Education Requirements
Master's or PhD in Electrical Engineering or Computer Science — or equivalent practical experience.
About the Company
Company: NVIDIA
Headquarters: Santa Clara, California, USA
NVIDIA is a global leader in accelerated computing, renowned for its innovative solutions in AI and digital twins that transform diverse industries. The company specializes in networking technologies, providing end-to-end InfiniBand and Ethernet solutions for servers and storage that optimize performance and scalability. NVIDIA serves sectors such as high-performance computing, enterprise data centers, and cloud computing, constantly reinventing its products and services to stay ahead in the market.
