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ASIC CAD Engineer, Clocks Methodology

Nvidia

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81 open methodology roles across 14 companies are on ApplySarthi right now, most of them in Hyderabad (8), Bengaluru (8), Delhi NCR (1).

What methodology roles keep asking for: Python (59%), Perl (37%), C++ (25%), Deep learning (15%) — counted across their open postings here.

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Questions you are likely to be asked

  1. Why do you want to join Nvidia?
  2. What is your experience with C++? Tell me one thing you learned the hard way.
  3. Describe a time a deadline forced a trade-off in quality. What did you choose and why?
  4. How would you design an API for a feature you have worked on?
  5. What do you do when a production issue happens on your code?

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NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation fueled by groundbreaking 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 GPUs power computers, robots, and autonomous vehicles that can understand and interact with the world. Achieving what has never been done before requires vision, innovation, and exceptional talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Join us and help make a lasting impact on the world. The Clocks Design Methodology Team develops advanced clocking methodologies and custom CAD solutions to address the increasing complexity and scale of next-generation chips. As part of the NVQuartz Team, we build scalable tools and methodologies that enable heterogeneous hardware designs across NVIDIA's product portfolio, including SoCs, CPUs, GPUs, and Networking products. Our mission is to improve engineering productivity, design quality, and scalability by developing innovative automation, validation frameworks, and methodologies used across the company. What You'll Be Doing: Own the validation of clocking methodology solutions for hardware clocking designs across multiple product lines. Understand design requirements and develop robust validation strategies, automation, quality checks, debug infrastructure, bug fixes, and productization workflows. Solve complex engineering problems by developing scalable methodology and automation solutions that work across multiple chip architectures. Develop and maintain tools using C++, Python, Perl, Tcl, and NVIDIA's internal compilers, frameworks, and CAD infrastructure. Partner closely with design, verification, architecture, and methodology teams to understand requirements and deliver high-quality tool capabilities. Collaborate with Quality Assurance engineers to ensure robust, production-ready methodology releases. Work effectively with engineering teams across multiple geographies and time zones. What We Need to See: BS or MS in Computer Science, Electrical Engineering, or a related field (or equivalent industry experience). 1+ years of experience and strong understanding of digital logic design and computer architecture. Solid software engineering skills with expertise in C/C++ and scripting languages such as Python, Perl, and Tcl. Experience developing CAD tools, engineering automation, or software infrastructure. Understanding of algorithms, data structures, and software design principles. Ability to work collaboratively across multiple engineering disciplines. Strong problem-solving skills and the ability to independently drive technical solutions. Experience building tools for hardware engineering teams is highly desirable. Exposure to VLSI design flows, clocking methodologies, or physical design is a plus. We have some of the most forward-thinking and hardworking engineers in the world, and our world-class engineering teams continue to grow rapidly. If you're creative, curious, passionate about technology, and excited to solve challenging problems at scale, we'd love to hear from you. #LI-Hybrid

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Listed on workday · posted 2026-10-12. ApplySarthi collects openings and links to application pages; the role is advertised by Nvidia, not by us.