Senior ASIC Timing Engineer
Nvidia
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This role on the market
24 open timing roles across 9 companies are on ApplySarthi right now, most of them in Bengaluru (1).
- ASIC Physical Design Engineer — Synthesis and Timing – (Associate or Experienced)Boeing
- Static Timing Analysis Design Engineer / Physical DesignNxp
- Physical Design Engineer- Static Timing Analysis (STA)IBM
- Timing & Power Analysis CAD EngineerMarvell · bengaluru
- Design Engineer - Timing MethodologyBroadcom
What timing roles keep asking for: Python (54%), Perl (29%), Deep learning (21%) — counted across their open postings here.
Nvidia has 3,820 open roles listed here.
- Software Developer - Networking
- Manager, Silicon Circuit and Power Integrity - Silicon Co-Design Group
- Senior Physical Design Methodology Engineerbengaluru
- Electro Optics Student
- Manager, Software Verification
Counted across 14 company job boards, updated as roles open and close.
Preparing for this interview
Interviews for timing roles keep coming back to Python, Perl, Deep learning. Practise those questions before you sit with Nvidia.
Questions you are likely to be asked
- Why do you want to join Nvidia?
- What is your experience with Deep learning? Tell me one thing you learned the hard way.
- How do you decide what to test, and what does good code review look like to you?
- Describe a time a deadline forced a trade-off in quality. What did you choose and why?
- How would you design an API for a feature you have worked on?
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Practise the Senior ASIC Timing Engineer at Nvidia interview free →NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world. 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: Lead the timing analysis and closure processes for NVIDIA's GPUs, CPUs, LPUs, and SoCs at block level, cluster level, and full chip level. Collaborate with Cross-Functional Teams: Work closely with RTL, DFX, Clocks, and other teams to devise timing closure strategies, create timing constraints, and drive timing and power convergence as well as implement ECOs. Contribute to Cutting-Edge Projects: Play a pivotal role in the success of our innovative projects and advancement of our technology. Leverage your expertise to improve timing convergence flows in collaboration with 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 3 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. Experience in physical design and optimization e.g., synthesis, placement, routing, logic restructuring, etc. to improve timing and power. 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, LPU or SOCs Background in logic synthesis and equivalence checking/FV. 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. #LI-Hybrid Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 136,000 USD - 218,500 USD for Level 3, and 168,000 USD - 264,500 USD for Level 4. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until October 9, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering an inclusive 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.
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Listed on workday · posted 2026-10-30. ApplySarthi collects openings and links to application pages; the role is advertised by Nvidia, not by us.