NVIDIA has continuously reinvented itself over two decades. Our invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing. NVIDIA is a "learning machine" that constantly evolves by adapting to new challenges that are hard to tackle, that only we can pursue, and that matter to the world. This is our life's work to amplify human inventiveness and intelligence. Choose to join us today.
NVIDIA Silicon Solutions Group seeks a hardworking engineer to join a silicon HW team. As a team member, you will develop and validate system-level features with a deep understanding of product needs that will be delivered to notebook, desktop, embedded, automotive, and professional solution markets. Prior experience in the lab with system-level post-silicon bring-up and debug is highly desired.
What you'll be doing:
Build roadmaps of memory system-level features to address low power, low noise, perf/watt efficient, and stable/reliable product needs by doing prototyping, use case analysis, and system-level cost/benefit tradeoff.
Architect, design, and integrate memory system-level features, controllers, and policies - including binning, pairing, and adaptive control techniques based on the roadmap to optimize product performance, power, and reliability/stability.
Collaborate with architecture, ASIC, board/platform design, software/firmware, marketing, and other multi-functional teams to drive architecture, design, and debug.
Expand power improvement initiatives to cover various products and market segments, including high-demand environments such as data centers. Drive scalable, power-efficient, and reliable memory system solutions across diverse platforms.
Keep track of the latest industry direction, market needs, and technology development; incorporate them into future roadmaps to build more competitive products.
Lead debug, craft WARs, and support bringup, validation, manufacturing, and customer issues on relevant features.
What we need to see:
BS or MS degree in EE/CE or equivalent experience.
8+ years of experience in memory subsystem architecture, design, and validation, with a strong focus on system-level features that optimize memory power for perf-per-watt efficiency in datacenter or high-perf systems.
Strong fundamentals in EE, digital/analog design, signal integrity, low power design, memory power management techniques, timing analysis, and architecture.
It is crucial to have a deep understanding of how system-level memory interacts with different IPs and SW/FW, including their impact on power, latency, and reliability.
Experience with control systems, boot/reset flows, and memory controller micro-architecture.
Validated hands-on lab experience with silicon bringup, lab debug, and lab tools (oscilloscopes, multimeters, logic analyzers).
Excellent problem-solving, teamwork, and interpersonal skills.
Experience with Python, Perl, C/C++, Windows, and Linux is a plus.
At NVIDIA, it's not just about technology—it's about people. Our culture, built on innovation, perfection, determination, and teamwork, drives us to be the best. NVIDIA is home to some of the brightest minds in the world, and we strive to further creativity and passion in everything we do. We want to hear from you if you're driven and ready to make an impact!
#LI-Hybrid
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 168,000 USD - 264,500 USD for Level 4, and 196,000 USD - 310,500 USD for Level 5.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 a diverse 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.Top Skills
What We Do
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”
