Software R&D Engineer — VLSI Physical Design (New College Grad 2026)
NVIDIAJob Title
Software R&D Engineer — VLSI Physical Design (New College Grad 2026)
Role Summary
Join a software team that builds high-performance internal EDA tools used to implement advanced AI hardware. The role focuses on research and development of VLSI physical-design optimization engines and algorithms to improve performance, power, and area (PPA).
The team works across algorithm invention, C++ implementation, and direct collaboration with chip design teams to deploy improvements into production flows.
Experience Level
Entry-level / New college graduate (targeting 2026 new grads). Suitable for candidates with internship or research experience in VLSI physical-design algorithms or equivalent practical experience.
Responsibilities
Contribute to algorithm design and implementation for VLSI physical design optimization and work with design teams to integrate and validate solutions.
- Invent and develop optimization engines that combine multiple physical-design steps (e.g., co-optimization of legalization and sizing) to improve chip frequency and reduce power.
- Design and implement 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 high performance: multithreading, memory and I/O efficiency, and distributed execution where applicable.
- Collaborate with chip design teams to validate algorithms on real designs and drive deployment into internal toolchains.
- Iterate on algorithms using data-driven methods and integrate ML techniques where beneficial.
Requirements
Core technical skills and domain knowledge required or strongly preferred.
- Experience developing VLSI physical-design algorithms in C++.
- Solid understanding of timing optimization and related concepts: cell libraries, interconnect models, crosstalk, glitches, IR drop, timing constraints, corners, and congestion.
- Familiarity with industry implementation and signoff tools and flows (examples: ICC2, Innovus, PrimeTime, Tempus, StarRC) and scripting in Perl, Tcl, or Python.
- Practical skills in high-performance software design: multithreading, concurrency, and efficient memory/I/O use.
- Strong problem-solving ability and drive to improve PPA through continuous refinement.
Nice-to-have:
- Experience with modern C++ (C++14 or newer), lambdas, and concurrency patterns.
- Experience applying ML (reinforcement learning, GNNs) to physical-design problems.
- Prior internship or project experience on advanced process-node designs or ML-assisted EDA tools.
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.
