Implementation Methodology Engineer, GPU

Nvidia

Confirmed live today High trust
Hybrid

Quick summary

Work type
Hybrid
Location
Santa Clara, CA
Salary
$136,000–$218,500 / yr
Employment
Full-time
Posted
161 days ago
Freshness
Confirmed live today

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $224k
This role $177k
$119k $295k
below market most similar roles pay here above market

This role pays less than 81% of similar roles. Most pay $196,750–$250,812 — the blue band above. At the midpoint, this role pays about $177k versus about $224k for comparable roles.

Based on 240 similar postings.

Employer

About Nvidia

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

TL;DR · Implementation Methodology Engineer, GPU

The Implementation Methodology Engineer joins the NVIDIA VLSI team to manage front-end design implementation methodologies, including synthesis and formal-equivalence-checking. The role involves flow automation, application support, and utilizing implementation flows to improve power, performance, and area on critical designs. The engineer will collaborate with logic designers, physical designers, and EDA vendors to solve technical issues and develop new solutions. Key requirements include expertise in logic optimization techniques, physical synthesis, placement, routing, and logic restructuring. Candidates must be power users of Synopsys DC/FC and Cadence Genus/Innovus tools. Preferred skills include proficiency in Python, Tcl, and Make scripting. This position addresses technical challenges in developing real-time, cost-effective computing platforms for domains such as Deep Learning, AI, Robotics, Autonomous Driving, Gaming, and High Performance Computing.

What you'll do

  • Manage all aspects of front-end design implementation methodologies including synthesis and formal equivalence checking.
  • Automate design flows and provide technical application support for internal teams.
  • Utilize EDA tool expertise to optimize power, performance, and area on critical designs.
  • Solve complex implementation issues by developing new technical solutions.
  • Provide technical support for various EDA tools and internal design flows.
  • Perform logic optimization and manage trade-offs between area, timing, and power.
  • Execute physical design tasks including physical synthesis, placement, routing, and logic restructuring.

What we're looking for

  • BS or MS in Electrical Engineering, Computer Engineering, or related fields (or equivalent experience).
  • 4+ years of experience in logic design implementation and/or physical design implementation.
  • Deep understanding of logic optimization techniques and relative area, timing, and power trade-offs.
  • Strong understanding of physical design implementation including physical synthesis, placement, routing, and logic restructuring.
  • Power user of synthesis and/or place and route EDA tools from Synopsys (DC/FC) and Cadence (Genus/Innovus).
  • Strong debugging, problem-solving, and interpersonal skills.
  • Prior experience in physical implementation (preferred).
  • Proficiency in Python, Tcl, and Make scripting (preferred).

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