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.
Help in driving frontend and backend implementation including synthesis, equivalence checking, floor-planning, timing constraints, timing and power convergence, and ECO implementation.
Work in a cross-functional environment interacting with multiple teams.
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 Synthesis and Timing
Hands-on experience in full-chip/sub-chip Static Timing Analysis (STA), timing constraints generation and management, and timing convergence.
Expertise in analysis and fixing of timing paths through ECOs including crosstalk and noise analysis.
Expertise in physical design and optimization e.g., placement, routing, cell sizing, buffering, logic restructuring, etc. to improve timing and power, along with a background in implementing them through ECOs.
Background in logic synthesis and equivalence checking/FV.
Expertise and in-depth knowledge of industry standard EDA tools.
Proficiency in programming and scripting languages, such as, Perl, Tcl, Python, etc.
Ways to stand out from the crowd:
Background in domain specific STA and timing convergence, such as CPUs, GPUs or Network processor implementation or SOCs.
Understanding of DFT logic and experience with DFT timing closure for various modes e.g., scan shift and capture, transition faults, BIST, etc.
Knowledge of deep sub-micron technology and associated process variations effects, including modeling and converging considering process variations.
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.
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.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
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.Similar Jobs
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.”
