Role at a glance
- Salary
- Not Disclosed
- Location
- 3 Locations, California, United States
- Work arrangement
- On-site
- Employment
- Full-time
- Experience
- 18+ years of relevant industry and/or academic experience.
- Education
- MSEE, MSCE, or PhD or equivalent experience demonstrating significant impact in Electrical Engineering, Computer Engineering, Computer...
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Qualifications
18+ years of relevant industry and/or academic experience. MSEE, MSCE, or PhD or equivalent experience demonstrating significant impact in Electrical Engineering, Computer Engineering, Computer Science, or a related field. The posting also calls for defining new technology frontiers; driving ML- and workload-aware modeling and post-silicon optimization; influencing across the company and industry; developing technical leaders; and generating sustained IP and intellectual contribution.
Preferred
- We would love to see if you have deep roots in RTL, microarchitecture, or backend implementation that allow you to operate fluently from...
About the role
Original posting provided by NVIDIA
Join NVIDIA's GPU memory architecture team and help define the DRAM and memory architecture of our Innovative silicon and systems across many domains. As a Distinguished Engineer, you'll develop the long-term technical strategy for Memory architecture including DRAM interfaces, SRAM requirements. This role impacts datacenter GPUs, GeForce and client products, automotive (DRIVE), robotics (Jetson, Isaac), and the broader edge-AI portfolio. We would lean on you to drive encompassing hardware, software interfaces, and micro-architectural considerations, to deliver significant application-level benefits. This role suits a recognized expert who has personally crafted the Memory architecture of multiple successful silicon generations and is ready to own the next decade of perf/watt advancement at NVIDIA. This is your chance to join a company that continually expands the possibilities of technology and innovation!
What you'll be doing:
- Set multi-generation, cross-portfolio Memory interface strategy.
- Drive performance-versus-power analysis that influences major silicon trade-offs and product roadmap decisions.
- Lead silicon and vendor/IP co-architecture.
What we need to see:
- Define new technology frontiers.
- Drive ML- and workload-aware modeling and post-silicon optimization.
- Influence across the company and the industry.
- Develop the next generation of technical leaders.
- Generate sustained IP and intellectual contribution.
- MSEE, MSCE, or PhD or equivalent experience demonstrating significant impact in Electrical Engineering, Computer Engineering, Computer Science, or a related field.
- 18+ years of relevant industry and/or academic experience.
Ways to stand out from the crowd:
- We would love to see if you have deep roots in RTL, microarchitecture, or backend implementation that allow you to operate fluently from architectural intent down to build realization with history of mentoring engineers into Principal and Distinguished-level roles, and of building durable technical communities in Memory architecture.
You will also be eligible for equity and benefits.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.About the company
NVIDIA
Large Enterprise
NVIDIA is a leading technology company renowned for its graphics processing units (GPUs) and innovative computing solutions that enhance visual experiences across multiple platforms, including gaming, scientific research, and artificial intelligence. Founded in 1993, the company has expanded its offerings to include powerful AI frameworks and deep learning platforms, making significant contributions to industries such as gaming, data centers, automotive, and healthcare. NVIDIA's commitment to pushing the boundaries of visual computing continues to drive advancements in both hardware and software, positioning the company at the forefront of emerging technologies and digital transformation.