Used Tools & Technologies
Not specified
Required Skills & Competences
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.
Software Development @ 7
Python @ 7
Communication @ 4
Data Analysis @ 4
Pandas @ 4
GPU @ 4
- 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 is seeking a world-class computer architect to contribute to the development of future high-performance GPU computing systems. The role focuses on memory and on-chip interconnect subsystems with an emphasis on improving performance, power, and area (PPA). Candidates should have deep experience in memory systems architecture, performance modeling, and large-scale software development.
Responsibilities
- Define and architect innovative features for next-generation GPU memory and on-chip interconnect subsystems.
- Develop, implement, and refine performance models to evaluate architectural choices and predict subsystem behavior.
- Develop and evaluate test cases to validate performance models and ensure robust feature integration.
- Analyze benchmarks, application workloads, and performance/power simulation and emulation results to identify areas for architecture optimizations.
- Collaborate closely with multi-disciplinary engineering teams to translate product requirements into architectural solutions.
Requirements
- Bachelor’s degree (or equivalent experience) in Computer Engineering, Electrical Engineering, Computer Science, or a related field with a minimum of 8+ years of relevant professional experience; OR MS with 6+ years; OR PhD with 4+ years.
- Understanding of CPU or GPU architecture, memory systems, or network-on-chip design.
- Experience in large-scale software development projects and strong programming skills in C/C++ and Python or other scripting languages.
- Experience developing and using performance/power simulation and emulation tools; ability to analyze simulation/emulation results.
- Experience developing and refining performance models and creating test cases within performance modeling frameworks.
- Strong analytical skills for benchmark and workload analysis.
- Excellent written and verbal communication skills for collaboration with internal teams and external partners.
Ways to stand out
- Background in parallel computing, datacenter architecture, or large-scale interconnect architecture.
- Expertise in data analysis and visualization using tools such as pandas.
- Experience writing, running, and analyzing test cases within performance modeling frameworks.
- Experience using AI tools for code development, validation, and analysis.
Compensation and Benefits
- Base salary ranges (depending on level and location):
- Level 4: 184,000 USD - 287,500 USD
- Level 5: 224,000 USD - 356,500 USD
- Eligible for equity and benefits. See: https://www.nvidiabenefits.com/
Other
- Applications for this job will be accepted at least until December 16, 2025.
- NVIDIA is an equal opportunity employer committed to diversity and inclusion.