NVIDIA Corporation

Senior STA Signoff Methodology Engineer

NVIDIA Corporation$168K — $310K *
Technical Services
8 - 10 years of experience
Job Overview by Ladders

Qualifications

  • MS in Electrical or Computer Engineering or equivalent, with 8 years in ASIC design and timing
  • Deep understanding of RC extraction, device physics, and STA methodologies
  • Solid foundation in mathematics and physics for electrical design
  • Experience with low-power techniques such as clock gating and DVFS
  • Knowledge of signal integrity and other physical effects impacting timing
  • Hands-on experience with advanced FinFET technologies at 5nm and below
  • Familiarity with ASIC tools like PrimeTime and ICC2

Responsibilities

  • Run large-scale SPICE simulations and STA experiments to impact chip timing
  • Develop STA and PNR flows addressing advanced-node physical effects
  • Collaborate with engineers to define sophisticated timing-signoff strategies
  • Develop tools that enhance design performance and silicon reliability
  • Work across STA, constraints, and power optimization
  • Perform extensive data analysis using Python or similar tools

Benefits

  • Eligible for equity
  • Flexible work schedule
  • Collaborative team environment
  • Opportunity to influence next-gen AI technologies
  • Access to cutting-edge tools and resources for development
Full Job Description
We are seeking an innovative Senior STA Signoff Methodology Engineer to help drive sign-off strategies for the world's leading GPUs, CPUs, LPUs and SoCs. This position is a broad opportunity to optimize performance, yield, and reliability through increasingly comprehensive modeling, insightful analysis, and automation. This work will influence the entire next generation AI landscape through critical contributions across NVIDIA's many product lines. We have crafted a team of highly motivated people whose mission is to push the frontiers of what is possible today and define the platform for the future of computing. If you are fascinated by the immense scale of precision, craftsmanship, and artistry required to make billions of transistors function on every die at technology nodes as deep as 3nm and beyond, this is an ideal role. What you'll be doing: • Run large-scale SPICE simulations and STA experiments to model the impact of advanced technologies on chip timing. • Develop STA and PNR flows and recommendations addressing aging, self-heating, thermal effects, IR drop, electro migration, and other advanced-node physical effects. • Collaborate with technology leads, physical-design engineers, and timing engineers to define and deploy sophisticated timing-signoff strategies for extraordinary silicon performance. • Develop tools and methodologies that improve design performance, predictability, and silicon reliability beyond the capabilities of standard EDA tools. • Work across STA, constraints, and timing and power optimization. • Perform extensive data analysis using Python, JMP, or similar tools to improve STA-to-silicon correlation. What we need to see: • MS in Electrical or Computer Engineering, or equivalent experience, with 8 years of experience in ASIC design and timing. • Solid understanding of RC extraction, device physics, STA methodologies, and EDA-tool limitations. • Proven foundation in the mathematics and physics underlying electrical design. • Experience with low-power techniques, including multi-Vt design, clock gating, power gating, activity-based power analysis, DVFS, and CDC. • Understanding of signal and power integrity, crosstalk, electromigration, noise, OCV, timing margins, clock jitter, and IR drop. • Understanding of standard-cell, memory, and I/O IP modeling and their use in ASIC flows. • Hands-on experience with advanced FinFET and emerging CMOS technologies at 5 nm, 3 nm, 2 nm, and beyond. • Familiarity with industry-standard ASIC tools such as PrimeTime, ICC2, RedHawk, and Tempus. • Strong communication skills and a collaborative working style. Ways to stand out from the crowd: • Familiarity with 3D IC integration, die stacking and packaging, self-heating, and their impact on timing closure. • Strong data-analysis and modeling skills employing Python, JMP, or similar platforms. • Proficiency in Tcl and Python; C++ experience is a plus. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 168,000 USD - 264,500 USD for Level 4, and 196,000 USD - 310,500 USD for Level 5. You will also be eligible for equity and . Applications for this job will be accepted at least until August 24, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes.

About NVIDIA Corporation

Nvidia, a global leader in graphics, gaming, and AI technology, offers Nvidia careers and internship opportunities for those passionate about driving innovation in the tech industry. you'll find a company committed to growth, teamwork, and leadership in computer science and machine learning domains.

About Nvidia

A Pioneer in Technology and Innovation

Nvidia has cemented its reputation as a powerhouse in developing advanced graphics processing units (GPUs) and has significantly contributed to the gaming industry's evolution. Moreover, its foray into AI and machine learning has opened new frontiers in technology, making Nvidia a beacon of innovation and a desirable workplace for ambitious tech professionals.

Job Opportunities

Diverse Positions in a Dynamic Field

Nvidia is continuously on the lookout for talented individuals across various domains, including hardware and software engineering, product design, marketing, and sales. Employment opportunities at Nvidia are vast, catering to a wide range of expertise and career aspirations.

Employment in Hardware and Graphics

For those fascinated by the intricacies of hardware and graphics technology, Nvidia offers positions that sit at the forefront of gaming and computing advancements.

Growth in Machine Learning and AI

Nvidia's leadership in AI and machine learning has created numerous vacancies for specialists eager to contribute to groundbreaking projects.

Recruitment in Computer Science

With the constant demand for innovation, Nvidia's recruitment efforts focus on computer science experts capable of pushing the boundaries of what's possible.

Internship Program

Opening Doors to Future Innovators

Nvidia's internship program is designed to nurture the next generation of technology leaders, offering hands-on experience in a culture that celebrates creativity and teamwork.

Benefits and Culture

Interns at Nvidia enjoy a plethora of benefits, from competitive stipends to mentorship opportunities, all within an environment that values growth and learning.

Opportunities for Students

Whether you're an undergraduate, a master's student, or a Ph.D. candidate, Nvidia's internships provide a real-world glimpse into the tech industry, offering valuable experience in various technology fields.

Pathways to Full-Time Employment

Many interns have transitioned into full-time positions, marking the start of successful careers at Nvidia. The internship program is more than a stepping stone into the company; it’s an investment in the professional development of interns. The goal is to ensure that interns are well-equipped for future challenges.

Nvidia Careers: More Than Just a Job

Nvidia offers more than just a job to its employees; it provides a front-row seat on the journey into the future of technology. Nvidia stands as a pillar of innovation with its vast opportunities in hardware, graphics, gaming, machine learning, and computer science. Nvidia careers serve as a launching pad for talented workers who aim to redefine the technological landscape. Whether through full-time positions or internships, joining Nvidia means contributing to a legacy of breakthroughs and becoming part of a global community dedicated to pushing the boundaries of what's possible.
Learn more about NVIDIA Corporation
Size
22,473 employees
Market Cap
$350.4 billion
Industry
Net Income
$4.3 billion
Founded
1993
5 Year Trend
+31.3%
Revenue
$16.6 billion
NASDAQ

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