Senior Timing Methodology Engineer 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

MS (or equivalent experience) in Electrical or Computer Engineering with 3 years’ experience in ASIC Design and Timing
Good understanding of modeling circuits for sign-off
Good knowledge of extraction, device physics, STA methodology and EDA tools limitations
Good understanding of mathematics/physics fundamentals of electrical design
Clear understanding of low power design techniques such as multi VT, Clock gating, Power gating, Block Activity Power, and Dynamic Voltage-Frequency Scaling (DVFS), CDC, signal/power integrity, etc
Understanding of 3DIC, stacking, packing, self-heating and its impact on timing/STA closure
Background with crosstalk, electro-migration, noise, OCV, timing margins
Familiarity with Clocking specs: jitter, IR drop, crosstalk, spice analysis
Understanding of standard cells/memory/IO IP modeling and its usage in the ASIC flow
Hands-on experience in advanced CMOS technologies, design with FinFET technology 5nm/3nm/2nm and beyond
Expertise in coding: TCL, Python. C++ is a plus
Familiarity with industry standard ASIC tools: PT, ICC, Redhawk, Tempus etc
Strong communications skills and good standout colleague

Responsibilities

Improve and validate flows for Prime-Time, Prime-Shield and Tempus STA QoR metrics for sign-off flow, and tool for high-speed designs, with focus on CAD and automation
Develop custom flows for validating QoR of ETM models, both of std cells and custom IPs
Develop flows/recommendations on STA sign-off to model deep submicron physical effects aging, self-heating, thermal impact, IR drop etc
Collaborate with technology leads, VLSI physical design, and timing engineers to define and deploy the most sophisticated strategies of signing off timing in design for world-class silicon performance
Develop tools, and methodologies to improve design performance, predictability, and silicon reliability beyond what industry standard tools can offer
Work on various aspects of STA, constraints, timing and power optimization

Skills

PrimeTime

PrimeShield

Tempus

STA

ETM

CAD

VLSI

Physical Design

Timing Analysis

Automation

IR Drop

Self-Heating

Aging

QoR

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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