Implementation Methodology Engineer
Nvidia
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How this pay compares to similar roles
This role pays more than 81% of similar roles. Most pay $151,168–$214,000 — the blue band above. At the midpoint, this role pays about $216k versus about $183k for comparable roles.
Based on 240 similar postings.
Employer
Nvidia is a leading designer of graphics processing units (GPUs) and system-on-chip units, powering gaming, professional visualization, data centers, and artificial intelligence workloads. Industry: Semiconductors & AI Computing
Nvidia currently has 1623 open roles on FindRole.
Listed pay typically runs $184,000–$287,500 across 1110 roles with salary data.
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At a glance
The Senior Implementation Methodology Engineer joins the elite VLSI team to own and improve the end-to-end RTL2GDS implementation methodology for advanced-node CPU builds. This role involves leading aggressive PPA optimization campaigns, evaluating new EDA tools, and developing next-generation efficiency automation to multiply engineering throughput. Key responsibilities include managing synthesis, place and route, CTS, and equivalence checking while serving as a technical liaison with vendors like Synopsys and Cadence. The candidate will build Python, TCL, and Perl automation frameworks to eliminate systemic bottlenecks and conduct rigorous A/B experiments to compare flow settings. Required expertise includes deep practical knowledge of the RTL2GDS flow, MCMM STA, and specific tools such as DC, ICC2, PrimeTime, Genus, and Innovus to solve complex timing closure and power issues.
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