Senior Deep Learning Software Engineer

Nvidia

Confirmed live today High trust

Quick summary

Work type: On-site
Location: Santa Clara, CAAustin, TXHillsboro, OR
Salary: $152,000–$241,500 / yr
Employment: Full-time
Posted: 64 days ago
Freshness: Confirmed live today
Nearby: 99+ roles within 25 mi

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Competitive pay

How this pay compares to similar roles

Similar $218k

This role $197k

$139k $277k

below market most similar roles pay here above market

This role pays less than 65% of similar roles. Most pay $194,450–$241,750 — the blue band above. At the midpoint, this role pays about $197k versus about $218k for comparable roles.

Based on 240 similar postings.

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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 Software Engineer

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The Senior Deep Learning Software Engineer, DLSim joins the DL Performance Modeling Team to develop simulation infrastructure for deep learning applications across various GPUs. This role involves developing simulation backends to enable fast, scalable evaluation of AI workloads across NVIDIA compiler stacks. You will improve deep learning compiler kernel code generation and computational graph optimization using analysis based on modeled scenarios and performance insights. Key responsibilities include advancing the modeling of datacenter-scale AI workloads and partnering with architects to evaluate future GPU features. The position requires hands-on experience with MLIR, compiler infrastructure, C/C++, and Python. You will utilize skills in software design, debugging, and performance analysis to solve technical problems related to AI-accelerating hardware and software advancements within the deep learning domain.

Skills

MLIR C++ Python Compiler Optimization NVIDIA Compiler Stack Computational Graph Optimization GPU LLM Inference Architectural Simulation Performance Analysis Software Design Debugging Test Development Intermediate Representations

What you'll do

Develop simulation backends for fast, scalable evaluation of AI workloads across NVIDIA compiler stacks.
Improve deep learning compiler kernel code generation and computational graph optimization.
Analyze modeled scenarios and performance insights to optimize compiler performance.
Advance the modeling and optimization of datacenter-scale AI workloads and deployment scenarios.
Evaluate future GPU features to guide silicon and system-level design decisions.
Build and maintain simulation infrastructure to assess new AI-accelerating hardware and software.

What we're looking for

Master's degree in Computer Science, Computer Engineering, or a related STEM field (or equivalent experience).
PhD in a related STEM field (preferred).
3+ years of relevant experience in compiler optimization, architectural simulation, or related areas.
Strong hands-on experience with MLIR and compiler infrastructure.
Excellent C/C++ and Python programming skills, including software design, debugging, performance analysis, and test development.
Strong communication and collaboration skills to thrive in a fast-paced, multi-functional environment.
Experience designing and building compiler frameworks or intermediate representations from the ground up (preferred).
Deep understanding of LLM inference workloads and their implications for computer architecture (preferred).

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