Senior Deep Learning Hardware Modeling Architect

Nvidia

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Hybrid

Quick summary

Work type: Hybrid
Location: CATXMA
Salary: $152,000–$241,500 / yr
Employment: Full-time
Posted: 82 days ago
Freshness: Confirmed live today
Nearby: 99+ roles within 25 mi

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Salary context

Competitive pay

How this pay compares to similar roles

Similar $211k

This role $197k

$139k $274k

below market most similar roles pay here above market

This role pays less than 58% of similar roles. Most pay $181,154–$241,750 — the blue band above. At the midpoint, this role pays about $197k versus about $211k 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 · Senior Deep Learning Hardware Modeling Architect

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The Senior Deep Learning Hardware Modeling Architect joins a team focused on hardware-software co-design to optimize AI inference speed and efficiency. In this role, you will drive architectural specifications to closure across multiple stakeholders and develop written specifications for key component-level and system-level designs. You will embody these specifications in an executable model used by many internal customers. Daily tasks involve ensuring high performance through C++ software practices, solid algorithms, data structures, and parallelism while resolving performance and correctness issues across chip and hardware subsystems. Required skills include expert C++ programming, RTL design, and architecture knowledge. You will work on modeling critical components of LLM inference solutions, addressing the technical challenges of pushing performance boundaries for large language model inference hardware.

Skills

C++ Hardware Modeling RTL Design LLM Inference Hardware-Software Co-design Algorithms Data Structures Parallelism Chip Design Profiling AI Inference

What you'll do

Drive architectural specifications to closure across multiple stakeholders.
Develop written specifications for key component-level and system-level designs.
Create executable models for key components using C++ software practices.
Implement high-performance algorithms and data structures to ensure system efficiency.
Utilize parallelism to optimize AI inference speed and performance.
Resolve performance and correctness issues across chip and hardware subsystems.
Work across teams to debug and fix hardware-software integration problems.

What we're looking for

BS or higher degree in a relevant field (CS, EE, Math) or equivalent experience.
5+ years of relevant experience.
Expert programming and software skills in C++.
Experience in RTL design and/or architecture with the ability to understand common chip design concepts.
An automation-centered mindset.
A desire to improve work efficiency using AI.
Experience with systems-level/architectural/chip modeling, profiling, and analysis (preferred).
Strong combined RTL and C++ skillset (preferred).

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