The Digital IP (DIP) group at NVIDIA is an organization of circuit design and CAD engineers that creates a wide variety of IP for the chips NVIDIA designs. This group works closely with internal SOC design, silicon testing, and productization teams that turn our IP into products that change the world. One of the roles fulfilled by the DIP group is to develop sophisticated SRAM compilers that are used extensively by our SOC design partners. We are looking to hire a skilled and creative SRAM circuit designer to help achieve these goals in a high-visibility position.
What you'll be doing:
- Embedded SRAM design: Transistor-level circuit design, supervising layout implementation, physical and logical verification, and debug of SRAM macros.
- SRAM compiler development: Envisioning, defining, and coding more efficient ways to automate the simultaneous assembly and validation of multiple unique SRAM macros using NVIDIA's extensive compute resources.
- Advanced development: Exploring the potential of future process nodes and developing techniques to achieve optimal power, performance, and area characteristics.
- Guiding SOC design, silicon test, and productization efforts: Collaborate with SOC design partners to help them achieve their overall performance and cost goals, guide the silicon test and characterization efforts, and working with productization teams to prepare new silicon for the demanding requirements of real-world applications.
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What we need to see:
- BSEE minimum (or equivalent experience), MSEE or PhD preferred
- 5+ years of SRAM design experience with a strong background in digital circuit design, layout, and validation on advanced FinFET processes
- Prior design experience in single-port, dual-port, or register file SRAM-based macros required, including complex circuits like self-timed logic and sense-amplifiers
- Python scripting ability to parse data and automate tasks
- Successful track record of delivering designs to production
Ways to stand out from the crowd:
- Self-motivation, attention to detail, and good written, verbal, and presentation skills are needed to success in this role
- A high degree of scripting expertise in Python
- Familiarity with Cadence schematic and layout capture tools
- Silicon testing/debug experience
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 that are hard to solve, that only we can take on, and that matter to the world. This is our life's work, to amplify human imagination and intelligence. Make the choice, join our diverse team today!