Senior Software Engineer, CUDA Deep Learning Systems

Nvidia

Confirmed live 2 days ago High trust
Remote

Quick summary

Work type
Remote
Location
Santa Clara, CAAustin, TX
Salary
$184,000–$287,500 / yr
Posted
11 days ago
Freshness
Confirmed live 2 days ago
Closes
Nov 1, 2026

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $207k
This role $236k
$162k most similar roles pay here $301k

This role pays more than 78% of similar roles. Most pay $178,150–$235,750 — the shaded band above. At the midpoint, this role pays about $236k versus about $207k 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 896 open roles on FindRole.

Listed pay typically runs $184,000–$287,500 across 876 roles with salary data.

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At a glance

TL;DR · Senior Software Engineer, CUDA Deep Learning Systems

As a Senior Software Engineer, CUDA Deep Learning Systems, you will join a research-oriented team focused on the intersection of deep learning architectures and low-level hardware optimization. You will research and prototype system optimizations for advanced models, architect distributed computing systems that scale from single nodes to supercomputer clusters, and develop custom high-performance CUDA kernels tailored to emerging neural network workloads. Your daily work involves analyzing hardware-software interactions to resolve bottlenecks in training and inference pipelines while collaborating with architects and compiler experts to improve memory bandwidth and communication efficiency. You will utilize C++, Python, and CUDA programming to optimize generative AI models, including large language models and diffusion models. The role addresses the technical challenge of maximizing accelerator compute utilization for complex deep learning frameworks like PyTorch and JAX through advanced kernel optimization and distributed machine learning techniques.

What does a Software Engineer earn in California?

Median $214000 from 775 postings across 63 companies.

See salary data

What you'll do

  • Research and prototype novel system optimizations at the intersection of deep learning frameworks and CUDA.
  • Architect and optimize distributed computing systems that scale from single nodes to large supercomputing clusters.
  • Design and implement custom high-performance CUDA kernels for emerging neural network architectures.
  • Analyze hardware-software interactions to identify and resolve performance bottlenecks in training and inference pipelines.
  • Develop exploratory tools and runtime systems to profile and accelerate new deep learning paradigms.
  • Write maintainable code for prototypes intended for open-source release, framework integration, or commercial products.

What we're looking for

  • BS, MS, or PhD degree in Computer Science, Computer Engineering, Electrical Engineering, or a related field.
  • 8+ years of relevant industry experience or equivalent academic experience after degree achievement.
  • Strong proficiency in C++ and Python programming.
  • Solid background in deep learning fundamentals with a focus on transformers.
  • Strong understanding of distributed computing principles, multi-node scaling, and cluster-scale execution performance challenges.
  • Proven experience in systems programming, computer architecture, and low-level systems performance optimization.
  • Hands-on experience with CUDA programming, kernel optimization, and workload profiling on GPU architectures.
  • Experience profiling and optimizing generative AI models, including large language models, vision models, or diffusion models.

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