Senior ASIC Timing 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

Semiconductor, TechnologyIndustries

Requirements

BS (or equivalent experience) in Electrical or Computer Engineering with 5 years experience or MS (or equivalent experience) with 2 years experience in Timing and STA
Hands-on experience in full-chip/sub-chip Static Timing Analysis (STA) and timing convergence, timing constraints generation and management
Expertise in analysis and fixing of timing paths through ECOs including crosstalk and noise analysis
Expertise and in-depth knowledge of industry standard STA and timing convergence tools
Knowledge of deep sub-micron process nodes and hands-on experience in modeling and converging timing in these nodes

Responsibilities

Drive timing analysis and closure of Nvidia’s GPUs, CPUs, DPUs and SoCs at block level, cluster level, and/or full chip level
Work with PD, DFX, Clocks, and other teams in coming up with timing closure strategy, creating timing constraints, driving timing and power convergence, as well as ECO implementation
Apply knowledge and experience to improve timing convergence flows working with the methodology teams

Skills

Key technologies and capabilities for this role

Static Timing AnalysisSTATiming ClosureTiming ConstraintsECO ImplementationPhysical DesignDFXClocksPower ConvergenceASIC Design

Questions & Answers

Common questions about this position

What education and experience are required for the Senior ASIC Timing Engineer role?

A BS (or equivalent experience) in Electrical or Computer Engineering with 5 years experience or MS (or equivalent experience) with 2 years experience in Timing and STA is required.

What are the key responsibilities of this position?

The role involves driving timing analysis and closure of Nvidia's GPUs, CPUs, DPUs and SoCs at block, cluster, and full chip levels, working with other teams on timing closure strategy, constraints, power convergence, and ECO implementation, and improving timing convergence flows.

What skills make a candidate stand out for this role?

Candidates stand out with background in domain specific STA for GPUs, CPUs, DPUs or SOCs, understanding of DFT logic and timing closure, experience with timing closure in AMS designs/IPs, and experience in methodology/flow development and automation.

What is the company culture like at NVIDIA?

NVIDIA is a dynamic, growing team focused on challenging problems in AI computing, with forward-thinking, hardworking, creative, and autonomous people working to amplify human inventiveness and intelligence.

Is this a remote position or does it require office work?

This information is not specified in the job description.

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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