Senior ASIC Timing Engineer

Posted 18 Days Ago
Be an Early Applicant
Santa Clara, CA
Senior level
Artificial Intelligence • Computer Vision • Hardware • Robotics • Metaverse
The Role
The Senior ASIC Timing Engineer will drive timing analysis and closure of GPUs, CPUs, and SoCs, collaborating with various teams to develop timing closure strategies and implement ECOs. Responsibilities include improving timing convergence flows and managing timing constraints for optimal performance.
Summary Generated by Built In

NVIDIA has continuously reinvented itself over two decades. Our invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing. NVIDIA is a “learning machine” that constantly evolves by adapting to new opportunities which are hard to solve, that only we can pursue, and that matter to the world. This is our life’s work, to amplify human inventiveness and intelligence.

We are now looking for a motivated ASIC Timing Engineer to join our dynamic and growing team. If you want to challenge yourself and be a part of something great, join us today! NVIDIA has continuously reinvented itself over two decades. Our invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing! More recently, GPU deep learning ignited modern AI — the next era of computing. NVIDIA is a “learning machine” that constantly evolves by adapting to new opportunities which are hard to tackle, that only we can pursue, and that matter to the world. This is our life’s work, to amplify human inventiveness and intelligence.

What you'll be doing:

  • 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.

What we need to see:

  • 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.

Ways to stand out from the crowd:

  • Background in domain specific STA and timing convergence, such as GPUs, CPUs, DPUs/Network processors, or SOCs

  • Understanding of DFT logic and experience with DFT timing closure for various modes e.g., scan, BIST, etc.

  • Understanding and timing closure of digital logic/macros in AMS designs/IPs.

  • Experience in methodology and/or flow development as well as automation.

NVIDIA is widely considered to be the leader of AI computing, and one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative and autonomous, we want to hear from you.

The base salary range is 136,000 USD - 264,500 USD. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions.

You will also be eligible for equity and benefits. NVIDIA accepts applications on an ongoing basis.

NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

Top Skills

Sta
The Company
HQ: Santa Clara, CA
21,960 Employees
On-site Workplace
Year Founded: 1993

What We Do

NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”

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