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NVIDIA

Mixed Signal Design Engineer - New College Grad 2025

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Santa Clara, CA, USA
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Santa Clara, CA, USA

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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 tackle, and that matter to the world. This is our life’s work, to amplify human creativity and intelligence. Make the choice and join us today!

This is a dynamic team working with innovative, unique technology. If you are someone that loves a challenge, come join this diverse team and help move the needle! We are looking for a senior engineer to be part of the mixed-signal design team building next generation NVLINK. This position offers the opportunity to have real impact in a dynamic, technology-focused company impacting product lines ranging from consumer graphics to self-driving cars and the growing field of artificial intelligence.

What you'll be doing:

  • Develop and implement high speed interfaces and analog circuits.

  • You will have hands on experience taking innovative integrated circuit designs for high-speed trans-receivers and PLLs.

  • Define circuit requirements and complete design from schematic, layout, and verification to characterization.

  • Conduct schematic design of deep-submicron CMOS technologies using Spectre, Hspice or like.

  • Take ownership for the architecture, transistor design and verification using industry standard EDA tools such as Cadence virtuoso.

  • Optimize circuit to meet the specifications for system performance.

  • Work closely with layout engineers by providing detailed floorplan and guidance for matching and high-speed routings.

  • Provide support for post-silicon bring-up and debugging.

What we need to see:

  • Pursuing a MS or PhD in Electrical Engineering, Computer Engineering, or related field with strong analog design background or equivalent experience

  • CMOS Analog / Mixed Signal Circuit Design Experience in deep sub-micron process (especially in FINFET)

  • Experience with design and verification tools (Cadence's IC design environment, analog circuit simulation tools like Spectre, HSpice, Finesim, XA)

  • Experience in crafting test bench environments for component and top-level circuit verification

  • Behavioral modeling of analog and digital circuits

  • Strong debugging and analytical skills

  • Analog simulation for noise analysis, loop stability analysis, ac/dc/tran analysis, monte-carlo, etc.

NVIDIA is widely considered to be 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! 

The base salary range is 108,000 USD - 212,750 USD. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions.

You will also be eligible for equity and benefits. NVIDIA accepts applications on an ongoing basis.

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.

HQ

NVIDIA Santa Clara, California, USA Office

2701 San Tomas Expressway, Santa Clara, CA, United States, Santa Clara

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  • Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
  • Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine

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