Power and Performance Engineer - System Memory at NVIDIA

Santa Clara, California, United States

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Not SpecifiedCompensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Semiconductors, Technology, AI, AutomotiveIndustries

Requirements

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
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
Prior experience in the lab with system-level post-silicon bring-up and debug is highly desired

Responsibilities

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

Skills

Post-Silicon Bring-Up

Debugging

Memory Systems

ASIC Design

Power Optimization

Perf/Watt Analysis

Prototyping

Adaptive Control

Firmware

System Validation

Controllers

Binning

Pairing

NVIDIA

Designs GPUs and AI computing solutions

About NVIDIA

NVIDIA designs and manufactures graphics processing units (GPUs) and system on a chip units (SoCs) for various markets, including gaming, professional visualization, data centers, and automotive. Their products include GPUs tailored for gaming and professional use, as well as platforms for artificial intelligence (AI) and high-performance computing (HPC) that cater to developers, data scientists, and IT administrators. NVIDIA generates revenue through the sale of hardware, software solutions, and cloud-based services, such as NVIDIA CloudXR and NGC, which enhance experiences in AI, machine learning, and computer vision. What sets NVIDIA apart from competitors is its strong focus on research and development, allowing it to maintain a leadership position in a competitive market. The company's goal is to drive innovation and provide advanced solutions that meet the needs of a diverse clientele, including gamers, researchers, and enterprises.

Santa Clara, CaliforniaHeadquarters

1993Year Founded

$19.5MTotal Funding

IPOCompany Stage

Automotive & Transportation, Enterprise Software, AI & Machine Learning, GamingIndustries

10,001+Employees

Benefits

Company Equity

401(k) Company Match

Risks

Increased competition from AI startups like xAI could challenge NVIDIA's market position.

Serve Robotics' expansion may divert resources from NVIDIA's core GPU and AI businesses.

Integration of VinBrain may pose challenges and distract from NVIDIA's primary operations.

Differentiation

NVIDIA leads in AI and HPC solutions with cutting-edge GPU technology.

The company excels in diverse markets, including gaming, data centers, and autonomous vehicles.

NVIDIA's cloud services, like CloudXR, offer scalable solutions for AI and machine learning.

Upsides

Acquisition of VinBrain enhances NVIDIA's AI capabilities in the healthcare sector.

Investment in Nebius Group boosts NVIDIA's AI infrastructure and cloud platform offerings.

Serve Robotics' expansion, backed by NVIDIA, highlights growth in autonomous delivery services.

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