Senior ASIC Timing Engineer

Reposted 14 Days Ago
Be an Early Applicant
Westford, MA
Senior level
Artificial Intelligence • Computer Vision • Hardware • Robotics • Metaverse
The Role
Drive physical design and timing for high-frequency, low-power DPUs and SoCs. Analyze design constraints, optimize performance, and manage timing convergence across various stages of chip development.
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.

NVIDIA is looking for best-in-class Senior ASIC Timing Design Engineers to join our outstanding Networking Silicon engineering team, developing the industry's best high speed communication devices, delivering the highest throughput and lowest latency! Come and take a part in crafting our groundbreaking and innovating chips, enjoy working in a meaningful, growing and professional environment where you make a significant impact in a technology-focused company.

What you will be doing:

  • You will drive physical design and timing of high-frequency and low-power DPUs and SoCs at block level, cluster level, and/or full chip level.

  • Analyze and optimize design constraints and synthesis parameters to achieve performance, power, and area targets.

  • Help in driving frontend and backend implementation from RTL to gds2, including synthesis, equivalence checking, floor-planning, timing constraints, timing and power convergence, and ECO implementation.

What we need to see:

  • Great teammate

  • BS (or equivalent experience) in Electrical or Computer Engineering

  • 8+ years experience or MS (or equivalent experience) with 2 years experience in Synthesis and Timing.

  • Understanding of DFT logic and hands-on experience in design closure.

  • Expertise in analyzing and converging crosstalk delay, noise glitch, and electrical/manufacturing rules in deep-sub micron processes.

  • Knowledge in process variation effect modeling and experience in design convergence taking into account process variations.

  • Experience in critical path planning and crafting needed.

  • Power user of Static Timing tools like Synopsys PrimeTime or Cadence Tempus.

  • Solid experience in full-chip/sub-chip Static Timing Analysis (STA), timing constraints generation and management, and timing convergence.

  • Proficiency in Python, Tcl and Make for automation and scripting tasks.

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 168,000 USD - 310,500 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

Cadence Tempus
Make
Python
Static Timing Tools
Synopsys Primetime
Tcl
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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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