About the role
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.
With the continuous improvement of chip technology, design scale and performance/power ratio, the physical design of digital chips is facing outstanding challenges in high frequency, low power consumption and multiple applications. High efficiency, high quality of the implementation of the construction chip is the guarantee of the company's competitiveness. As an ASIC-PD engineer at NVIDIA, you'll be responsible for the stage from RTL frozen to tape out, include synthesis, formal verification, constraints definition, timing closure/sign off, study on the timing impact of process and related methodology work. You will face the biggest challenge based on the most advanced process on building chips in the world.
What you'll be doing:
Chip integration and netlist generation
Synthesis
RTL/netlist quality check, Formal Verification, constraints creation and validation, timing budget.
Work with ASIC team to analyze/resolve special timing issues.
Cross-Team collaboration to implement chip partitioning and floorplan
Work in conjunction with PR engineers to achieve timing closure for both partition and full chip level; Achieve special mode timing closure, such as io, test, clock, async etc.
Function eco creation; Develop and improve entire timing closure flow from frontend (pre-layout) to backend (post-layout)
Flow automation development for above areas; Methodology in any of above areas.
What we need to see:
MS in EE or Microelectronics is preferred
2+ years of project experience in IC design implementation
Courses taken in circuit design, digital design
Hand-on experience in EDA software from Synopsys (DC/PT/Formality), Cadence (RC compiler/LEC) is helpful
Proficient user of Python or TCL is helpful
Proficient in English reading and writing
With competitive salaries and a generous benefits package, NVIDIA is widely considered to be one of the most desirable employers in the world. We have some of the most brilliant and talented people in the world working for us. If you are creative, autonomous and love a challenge, we want to hear from you. We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
Skills & Tags
Aplyr's read
NVIDIA is a pioneering force in GPUs and AI, attracting top talent in engineering and innovation-driven roles across various tech domains.
What's promising
- •NVIDIA leads the GPU market, crucial for gaming and AI applications.
- •The company invests heavily in AI and deep learning, driving technological advancements.
- •NVIDIA's strong market position offers stability and growth opportunities for employees.
What to watch
- •High competition in the semiconductor industry can impact market share.
- •Rapid technological changes require constant adaptation and learning.
- •Intense workload and high expectations may affect work-life balance.
Why NVIDIA
- •NVIDIA's GPUs are industry benchmarks in gaming and professional graphics.
- •The company's AI research is at the forefront of deep learning innovation.
- •NVIDIA's culture emphasizes cutting-edge technology and engineering excellence.
Aplyr’s read is generated by AI from public sources. Was it useful?
About NVIDIA
NVIDIA is a leading technology company known for its graphics processing units (GPUs) for gaming and professional markets, as well as its advancements in artificial intelligence and deep learning.
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