NVIDIA has continuously reinvented itself. Our invention of the GPU sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. Today, research in artificial intelligence is booming worldwide, which calls for highly scalable and massively parallel computation horsepower that NVIDIA GPUs excel. NVIDIA is a “learning machine” that constantly evolves by adapting to new opportunities that are hard to solve, that only we can address, and that matter to the world. This is our life’s work , to amplify human creativity and intelligence. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join our diverse team and see how you can make a lasting impact on the world!
NVIDIA is looking for a best-in-class ASIC STA Engineer to join our outstanding Networking Silicon engineering team, developing the industry's best high-speed communication devices, delivering the highest throughput and lowest latency for today's AI platforms! Come and take a part in designing our groundbreaking large scale and innovating chips, enjoy working in a meaningful, growing and highly professional environment where you make a significant impact in a technology-focused company.
What you will be doing:
Be in charge of full chip and/or chiplet level STA convergence from early stages to signoff.
Take part in top level floor plan and clock planning.
Optimize, together with CAD signoff flows and methodologies.
Digital Partitions' and analog IPs' timing integration, giving feedback to PD/RTL and driving convergence.
Work closely with logic design and DFT engineers to define and implement constraints for the various work modes, including their optimization for runtime and efficiency.
What we need to see:
B.SC./ M.SC. in Electrical Engineering/Computer Engineering.
3+ years of experience in physical design and STA
Proven experience in RTL2GDS and STA design and convergence
Familiarity with physical design EDA tools (such as Synopsys, Cadence, etc.)
Hands on STA experience from early stages to signoff using Synopsis Primetime. Deep knowledge in timing concepts required.
Great teammate.
NVIDIA has some of the most forward-thinking people in the world working for us. Are you a creative and autonomous engineer who loves a challenge? Are you ready to become the engineer you always wanted to be? Come and be part of the best physical design team in the industry!
#LI-Hybrid
Skills Required
- B.Sc./M.Sc. in Electrical Engineering or Computer Engineering
- 3+ years of experience in physical design and STA
- Proven experience in RTL2GDS and STA design and convergence
- Familiarity with physical design EDA tools (e.g., Synopsys, Cadence)
- Hands-on STA experience from early stages to signoff using Synopsys Primetime
- Deep knowledge of timing concepts
- Strong teamwork and collaboration skills
NVIDIA Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.
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Equity Value & Accessibility — Equity awards and a discounted ESPP are highlighted as core parts of total compensation, enabling employees to share in the company’s success. Stock-based compensation and the two-year lookback ESPP are consistently described as especially valuable.
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Healthcare Strength — Health coverage is portrayed as robust, with comprehensive medical, dental, and vision options alongside mental health support and on-site care resources. Employer HSA contributions and wellness perks reinforce the depth of the offering.
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Retirement Support — Retirement programs are depicted as strong, featuring a meaningful 401(k) match with Roth options and support for Mega Backdoor Roth contributions. These elements position long-term savings as a notable advantage of the total rewards package.
NVIDIA Insights
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.”
