Full-Time

Senior Timing Methodology Engineer

Confirmed live in the last 24 hours

NVIDIA

NVIDIA

10,001+ employees

Designs GPUs and AI computing solutions

Automotive & Transportation
Enterprise Software
AI & Machine Learning
Gaming

Compensation Overview

$136k - $264.5kAnnually

+ Equity

Senior

Company Historically Provides H1B Sponsorship

Austin, TX, USA + 1 more

More locations: Santa Clara, CA, USA

Category
Control Systems Engineering
Embedded Systems Engineering
Electrical Engineering
Required Skills
CAD
Python
C/C++

You match the following NVIDIA's candidate preferences

Employers are more likely to interview you if you match these preferences:

Degree
Experience
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.
  • Understanding 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 skill 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.

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. Unlike many competitors, NVIDIA focuses heavily on research and development to maintain its leadership in technology and innovation. The company's goal is to drive advancements in AI and computing to provide effective solutions for a wide range of clients, from gamers to enterprises.

Company Size

10,001+

Company Stage

IPO

Total Funding

$19.5M

Headquarters

Santa Clara, California

Founded

1993

Simplify Jobs

Simplify's Take

What believers are saying

  • NVIDIA's partnership with Together AI enhances its influence in AI infrastructure.
  • Backing GamerBoom shows NVIDIA's potential in the growing Web3 gaming sector.
  • Serve Robotics' expansion reflects demand for AI-driven urban logistics solutions.

What critics are saying

  • Lambda's funding could increase competition for NVIDIA's cloud services.
  • ClustroAI's edge AI technology may challenge NVIDIA's cloud-based solutions.
  • xAI's growth could create competitive tensions with overlapping AI solutions.

What makes NVIDIA unique

  • NVIDIA leads in AI and HPC with cutting-edge GPU technology.
  • The Omniverse platform expands NVIDIA's reach in digital twin and industrial AI markets.
  • NVIDIA's investment in edge AI aligns with trends in local device processing.

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Benefits

Company Equity

401(k) Company Match

Growth & Insights and Company News

Headcount

6 month growth

0%

1 year growth

0%

2 year growth

-1%
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