Published Date: January 22, 2026
NVIDIA, Santa Clara, CA 95050
Job Description:
Nvidia is seeking a Senior SOC/IP Methodology Engineer to design and architect next-generation custom SoC/IP solutions. The ideal candidate will have a passion for innovation and a deep understanding of SoC systems, client requirements, and development cycles. This role involves collaboration with internal and external partners to optimize methodologies and ensure high-quality product delivery.
Responsibilities:
- Develop and optimize semi-custom RTL to GDS methodologies.
- Collaborate with internal and external partners on SOC/IP requirements and technology alignments.
- Act as a hands-on domain expert from synthesis to final design closure.
- Engage with customers on SOC/IP development processes and quality assurance.
- Drive technical design reviews and improve development processes with innovative tools.
- Manage results and handoffs to and from customers, ensuring methodology solutions and schedule plans are met.
- Conduct early PPA on customer IP and perform what-if experiments to meet KPI targets.
- Execute floorplan experiments to drive area estimates and evaluate solution tradeoffs.
- Work with Nvidia's PD design methodology team to integrate external customer IP.
- Collaborate with external ASIC companies for outsourced design components.
Qualifications:
- Master's degree with 8+ years of experience or Bachelor's degree with 10+ years of equivalent experience.
- Extensive leadership experience in physical design methodology and technical expertise.
- Experience in SOC development and customer-focused environments.
- Proven ability to handle complex IP ecosystems with internal and external partners.
- Hands-on experience with RTL-to-GDSII tool flows and EDA vendor tools.
Skills:
- Strong background in Synthesis, CTS, Power Optimization, Placement, and Route methods.
- Proficient in scripting languages such as Python, Perl, and Tcl.
- Excellent interpersonal and soft skills.
- Experience with high-performance designs like CPU, GPU, and machine learning IPs.