> Markdown version of [/jobs/ext/2283692-software-r-d-engineer-vlsi-physical-design-new-college-grad-2026](https://www.wearedevelopers.com/jobs/ext/2283692-software-r-d-engineer-vlsi-physical-design-new-college-grad-2026). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Software R&D Engineer, VLSI Physical Design - New College Grad 2026 - **Company:** NVIDIA Corporation - **Location:** Austin, TX, United States - **Experience:** Starter - **Salary:** $116,000.0 - $189,750.0 - **Contract:** Permanent contract - **Skills:** Very-Large-Scale Integration, Artificial Neural Networks, C++ (Programming Language), Distributed Systems, Electronic Design Automation, Perl (Programming Language), Python (Programming Language), Machine Learning, Tensorflow, Software Engineering, Tcl (Programming Language), Reinforcement Learning, Multithreading, Parallel Computation, Information Technology, Vlsi Design, Hardware Acceleration, Physical Design, Cts+, C++14 - **Published:** August 28, 2026 - **Apply:** https://nvidia.wd5.myworkdayjobs.com/NVIDIAExternalCareerSite/job/US-TX-Austin/Software-R-D-Engineer--VLSI-Physical-Design---New-College-Grad-2026_JR2019330 ## About the Role * Masters or PhD in Electrical Engineer or Computer Science (or equivalent experience). * Experience with VLSI algorithms development using C++. * Understanding of VLSI timing optimization and related concepts, including cell libraries, interconnect models, crosstalk, glitches, IR drop, timing constraints, corners, congestion, etc. * Familiarity with design implementation tools such as ICC2, Innovus, PrimeTime, Tempus, and StarRC and typical design flows written in Perl, Tcl, and Python. Ways to stand out from the crowd: * C++14 or newer experience, such as lambdas and concurrency. * Understanding of how multiple Physical Design steps interact and how they can potentially be fused together to form hybrid engines that result in better PPA. * Experience in high performance software design including multithreading, distributed computing, efficient memory and I/O use, etc. * Highly driven to craft software towards improving PPA with a dedication to continuous improvement. * Experience with reinforcement learning, GNNs (Graph Neural Networks), and other relevant machine learning frameworks, especially as applied to physical design. ## Description NVIDIA's success builds on a foundation of industry leading hardware. We achieve distinction through extensive design optimization, including combining the best of external EDA with highly optimized, internal EDA tools. Our team develops these tools by fusing advances in parallel computing, machine learning, and specialized algorithms for VLSI design. We are seeking a R&D Software Engineer with proven experience in multiple areas of VLSI Physical Design Algorithms (sizing, buffering, CTS, legalization, incremental place and route etc.). Understanding both software and hardware aspects is the key. Creativity and self-drive to explore and perfect fast, high-capacity software is required. If you like to work across many technical areas and see your successes directly realized in the world's best AI hardware, it does not get any better than this! Developing software within a leading hardware company means getting to almost exclusively focus on the latest processes and most advanced designs. We're not bogged down by legacy support, niche roles, or convoluted approval processes. Our developers enjoy unusually high intellectual freedom and the ability to explore broad roles. What you'll be doing: * Invent new optimization engines that fuse traditionally independent engines (e.g., co-optimization of legalization and sizing) with the objective of increasing chip frequency while minimizing power consumption across a suite of internal optimization tools. * Improve algorithms (in C++) for gate-level sizing, buffering, useful clock skew, cell legalization, power minimization, ECO routing, and incremental parasitic extraction. * We as a team own the whole process from discovery and invention of new optimization opportunities, to developing solutions and working directly inside design teams to facilitate deployment. ## Related Videos - [Machine learning in the browser with TensorFlowjs](https://www.wearedevelopers.com/videos/155-machine-learning-in-the-browser-with-tensorflowjs) - [Coffee with Developers - Stephen Jones - NVIDIA](https://www.wearedevelopers.com/videos/1303-coffee-with-developers-stephen-jones-nvidia) - [How We Built a Machine Learning-Based Recommendation System (And Survived to Tell the Tale)](https://www.wearedevelopers.com/videos/752-how-we-built-a-machine-learning-based-recommendation-system-and-survived-to-tell-the-tale) - [Strange New Worlds: shaping the future of the digital age](https://www.wearedevelopers.com/videos/677-strange-new-worlds-shaping-the-future-of-the-digital-age) - [Accelerating Python on GPUs](https://www.wearedevelopers.com/videos/859-accelerating-python-on-gpus) - [Overview of Machine Learning in Python](https://www.wearedevelopers.com/videos/840-overview-of-machine-learning-in-python) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [How software is steering vehicle technology](https://www.wearedevelopers.com/magazine/515-how-software-is-steering-vehicle-technology) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [The Fastest-Growing Tech Sectors to Look Out for in 2025](https://www.wearedevelopers.com/magazine/373-the-fastest-growing-tech-sectors-to-look-out-for-in-2025) - [Résumé-Driven Development: How IT trends affect the job market for software developers](https://www.wearedevelopers.com/magazine/59-resume-driven-development-how-it-trends-affect-the-job-market-for-software-developers)