DFX Engineering
Overview
- Added in 30 days
- 647
- At this company, still open
Skills named in this posting
- Verilog
- DFT
- Python
- Tcl
- Perl
NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 30 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.
What you'll be doing:
• DFX planning, implementation, verification and silicon bring up at IP or fullchip level for NVIDIA's semiconductor products
• Take lead role of some DFX areas in a project
• Improve DFX design, architecture and flow
What we need to see:
• MSEE with 3+ years of experience or PhD in DFT or related domains
• Familiar with Verilog and ASIC design
• Proven knowledge and expertise in JTAG, Scan, ATPG, fault models and ATE testing, etc.
• Excellent analytical skills in verification and validation of test patterns and logic on sophisticated VLSI designs
• Experience in silicon debug and bring-up on the ATE with an understanding of pattern formats, failure processing and diagnostics
• Strong programming and scripting skills in Perl, Python or Tcl desired
• Outstanding written and oral communication skills in English with the curiosity to work on rare challenges
Apply on the employer's site
Original posting: jobs.nvidia.com
RISC-V ecosystem
NVIDIA Corporation in the RISC-V ecosystem
RISC-V International: Premier Board
Founded in 1993, NVIDIA is an AI computing company. The company is headquartered in Santa Clara, California.
- NVIDIA is bringing CUDA platform support to RISC-V, i.e. allowing a RISC-V CPU to host CUDA GPU applications
- Publicly credited the RVA23 profile as the enabler: "We wouldn't have considered porting CUDA to RISC-V without it"
- Active in RISC-V International profile/standards work and a frequent presence in RISC-V ecosystem coverage
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