Senior Timing Methodology Engineer, Custom Circuits 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, GPU, AI, AutomotiveIndustries

Requirements

MS (or equivalent experience) in Electrical or Computer Engineering with 5+ years experience in ASIC Design and Timing
Proven understanding of circuit design and spice simulations
Hands-on experience in advanced CMOS technologies, design with FinFET technology 5nm/3nm/2nm and beyond
Good understanding of circuit design styles in CMOS: domino circuits, high speed clocking, clock muxing circuits etc and how to verify them at circuit level in both spice and transistor level sta
Understanding crosstalk, noise, OCV, timing margins
Familiarity with Clocking specs: jitter, IR drop, crosstalk, spice analysis
Good understanding of .libs and usage of .libs in Nanotime as well as PT
Expertise in coding- TCL, Python
Hands-on experience with NanoTime static timing analysis, its algorithms and associated circuit constraint checks
Ability to navigate Cadence Virtuoso schematics
Familiarity with industry standard ASIC tools: PT, etc
Strong communications skills and good standout colleague

Responsibilities

Develop Timing sign-off flows, constraints and QOR metrics for custom macro design at transistor level along with ones using standard cells and custom designs
Validate the timing of custom circuit design using NanoTime and various spice simulations
Validate ETM models
Apply variation and statistical parameters in timing-analysis, including POCV, AOCV, Moments, wire-variation etc
Generate QOR data including IR drop, PVT and impact of variation models

Skills

Timing Analysis

NanoTime

SPICE Simulations

ETM Models

POCV

AOCV

Custom Circuits

Transistor Level Design

Standard Cells

QOR Metrics

IR Drop

PVT

Sign-off Flows

Constraints

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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