below marketmost similar roles pay hereabove market
This role pays less than
81%
of similar roles. Most pay
$151,913–$235,750
— the blue band above.
At the midpoint, this role pays about
$143k
versus about
$194k
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
1463 open roles
on FindRole.
Listed pay typically runs
$184,000–$287,500
across 1096 roles with salary data.
JOB TITLE: Systems Software Engineer, AI and Cloud - New College Grad 2026
As a Systems Software Engineer, AI and Cloud - New College Grad 2026, you will join a team focused on developing cloud-native, full-stack applications using microservices architecture to power AI use cases. Your daily responsibilities include designing and implementing agentic workflows using Retrieval-Augmented Generation, evaluating technical performance of AI solutions, and developing developer-focused content like tutorials and code samples. You will utilize Python, JavaScript, and C++ while working with frameworks such as vLLM, NVIDIA Triton Inference Server, and TensorRT. The role requires building scalable, production-ready inference systems optimized for Kubernetes deployment. You will solve complex problems in AI software architecture by creating technical whitepapers, running product demos, and collaborating across hardware and software engineering teams to improve product offerings.
What does a Systems Software Engineer earn in California?
Median $235750 from 32 postings across 3 companies.
Evaluate cloud-native, full-stack applications using microservices architecture to power AI use cases.
Design and implement agentic workflows using Retrieval-Augmented Generation (RAG) and advanced AI models.
Analyze technical performance of AI solutions and compile findings into comprehensive reports.
Provide practical product improvement suggestions to senior executives and engineering management.
Develop developer-focused content including detailed tutorials and code samples for NVIDIA tools.
Write technical whitepapers and product briefs for the company.
Run technical demos of NVIDIA products at prominent industry conferences.
What we're looking for
A Bachelor’s or Master’s in Software Engineering, Computer Science, Computer Engineering, Electrical Engineering, or a related degree (or equivalent experience).
Proficiency in Python and JavaScript for programming and debugging.
Strong foundation in data structures, algorithms, and software design principles.
Basic familiarity with C++ programming and its application in high-performance computing environments.
Experience crafting cloud-native systems optimized for Kubernetes deployment using inference frameworks like vLLM and NVIDIA Triton Inference Server.
Solid understanding of API design principles for building scalable, production-ready inference systems.
Advanced knowledge of LLMs, modern AI software architecture, and cloud APIs (preferred).
Contributions to public-facing technical content and open-source projects (preferred).
CUDA
GPU
Deep Learning
Distributed Computing
Parallel Programming
Algorithm Development
Data Structures
Memory Management
Model Optimization
Backpropagation
semiconductor manufacturing
Computational Geometry
Low-level Performance Optimization