Tech Stack
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
AI @ 4
Algorithms @ 7
Data Structures @ 7
Debugging @ 4
HPC
LLM
Machine Learning
Python @ 7
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
NVIDIA's Advanced Package Engineering team develops automation infrastructure for advanced multi-die packages connecting chiplets across substrates, interposers, and heterogeneous interfaces. This role focuses on creating production-grade EDA tooling and design flows for NVIDIA's next-generation AI and HPC platform packages.
Responsibilities
- Work with engineers to design and implement VLSI tools for silicon and substrate design.
- Develop maintainable, easy-to-use applications for project engineers.
- Develop flows, tools, and methodologies to construct, analyze, and validate package designs at different stages of the production flow.
- Optimize the daily workflows of package designers.
Requirements
- Bachelor's degree in Computer Science, Electrical Engineering, or a related field, or equivalent experience.
- 5+ years of flow and methodology development experience building package-design flows used by engineering teams at scale.
- Strong programming fundamentals in Python and/or C++, including data structures, algorithms, object-oriented design, and code-quality practices.
- Demonstrated experience applying AI/ML techniques in engineering workflows, such as using LLMs for code generation and debugging, building ML-assisted design-analysis tools, or integrating AI-assisted flows into EDA environments.
- Strong understanding of electrical engineering fundamentals relevant to VLSI package design, including signal integrity, power delivery, and parasitic extraction, or equivalent knowledge.
Preferred Qualifications
- Understanding of VLSI package design, interposer design, and IC physical design.
- Strong expertise in developing package-design flows and methodologies.
Benefits
- Competitive salary and comprehensive benefits package.
- Eligibility for equity and benefits.
- NVIDIA is committed to an inclusive work environment and is an equal opportunity employer.
Applications will be accepted at least until July 31, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes.
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