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60 Nvidia Ai Software Engineer Jobs Hiring Near You

Nvidia

Senior Full-Stack Lead Engineer

Santa Clara, CA · On-site

We're looking for a Senior Full-Stack Software Engineer to join the AI Hub team within the DGX Cloud AI Infrastructure organization. The AI Hub team accelerates AI research by ensuring NVIDIA's AI ...

Nvidia

Senior Full-Stack Lead Engineer

Seattle, WA · On-site

We're looking for a Senior Full-Stack Software Engineer to join the AI Hub team within the DGX Cloud AI Infrastructure organization. The AI Hub team accelerates AI research by ensuring NVIDIA's AI ...

Nvidia

OR · On-site

$108K - $147K/yr

Joining NVIDIA's DGX Cloud AI Efficiency Team means contributing to the infrastructure that powers ... We are seeking an AI infrastructure software engineer to join our team. You'll be instrumental in ...

NVIDIA Corporation

AI Software Engineer

Santa Clara, CA · On-site

$168 - $322/hr

We are seeking an AI Engineer to design and build intelligent systems that transform how we do ... NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity ...

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Nvidia Jobs Information

What is it like to work at Nvidia?

Nvidia is known for its collaborative and innovative culture, prioritizing teamwork and creativity to drive technological advancements. The company's structure is organized into various teams, including research and development, engineering, and sales, with a focus on fostering open communication and knowledge sharing across departments. Working at Nvidia may appeal to candidates who are passionate about artificial intelligence, graphics, and high-performance computing, as the company offers opportunities to contribute to cutting-edge projects and collaborate with experts in the field.

What makes Nvidia an attractive place to work?

Nvidia is a leading technology company in the field of artificial intelligence, graphics processing units, and high-performance computing, with a strong reputation for innovation and industry leadership. The company's workplace culture values collaboration, creativity, and innovation, with opportunities for employees to work on cutting-edge projects and contribute to the development of groundbreaking technologies. Joining Nvidia offers professionals a chance to be part of a dynamic and forward-thinking organization, with opportunities for growth, professional development, and making a meaningful impact in the tech industry.

Do workers at Nvidia get paid breaks?

Sometimes. Only some people get paid breaks.
45% of people say they don’t get paid breaks.
Based on data from 11 people who took the Breakroom Quiz between December 2024 and June 2026.

Does Nvidia pay people when they’re sick?

Yes. Most people get paid when they’re sick.
75% of people say they would get paid if they were sick but scheduled to work.
Based on data from 16 people who took the Breakroom Quiz between December 2024 and June 2026.

At Nvidia, are sick days and vacation days separate paid time off?

Sick days and vacation days are separate paid time off.
92% of people say they don’t have to use vacation days when they’re out sick.
Based on data from 13 people who took the Breakroom Quiz between June 2025 and June 2026.

Is the health insurance from Nvidia affordable enough for their workers?

Most people say the health insurance costs are okay.
100% of people say the health insurance costs are okay
Based on data from 12 people who took the Breakroom Quiz between June 2025 and June 2026.

Do people get paid time off at Nvidia?

Most people get paid time off work.
100% of people say they get paid time off.
Based on data from 13 people who took the Breakroom Quiz between June 2025 and June 2026.

How far ahead of time do people find out their work schedule?

Only some people find out their schedule four weeks ahead of time.
  • 67% of people with changing schedules find out their shifts one week or less ahead of time.
  • 0% of people with changing schedules find out their shifts two weeks ahead of time.
  • 0% of people with changing schedules find out their shifts three weeks ahead of time.
  • 33% of people with changing schedules find out their shifts four weeks or more ahead of time.

Based on data from 6 people who took the Breakroom Quiz between April 2025 and March 2026.

Do workers at Nvidia worry about hours?

Most people don’t worry about getting enough hours.
83% of people report they don’t worry about getting enough hours.
Based on data from 12 people who took the Breakroom Quiz between December 2024 and March 2026.

Do Nvidia workers get to choose the shifts they work?

Some people don’t get to choose which shifts they work.
40% report that they don’t have enough control over which shifts they work.
Based on data from 5 people who took the Breakroom Quiz between December 2024 and January 2026.

How easy is it for Nvidia workers to change shifts?

Most people find it easy to change shifts.
88% of people report that it’s easy to change shifts if they need to.
Based on data from 8 people who took the Breakroom Quiz between January 2025 and March 2026.

How easy is it to get time off at Nvidia?

Most people find it easy to get time off.
100% of people report it’s easy to get time off.
Based on data from 17 people who took the Breakroom Quiz between December 2024 and June 2026.

Do Nvidia managers change schedules at the last minute?

Most managers don’t change people’s schedules at the last minute.
92% of people say their manager doesn’t change their shift schedule at the last minute.
Based on data from 13 people who took the Breakroom Quiz between December 2024 and March 2026.

Do jobs at Nvidia spill into time workers aren’t paid for?

Rarely. The job doesn't usually spill into unpaid time.
17% of people report that their job takes up time that they don’t get paid for.
Based on data from 12 people who took the Breakroom Quiz between December 2024 and March 2026.

How easy is it to take sick days at Nvidia?

Most people find it easy to take sick days.
100% of people report that it’s easy to take time off if they are sick.
Based on data from 17 people who took the Breakroom Quiz between December 2024 and June 2026.

Do people at Nvidia feel treated with respect by their managers?

Most people feel treated with respect by their managers.
100% of people say they’re treated with respect by their managers.
Based on data from 16 people who took the Breakroom Quiz between December 2024 and June 2026.

Do people at Nvidia get to take their breaks without interruption?

Most people get breaks without interruption.
94% of people report that they get to take their breaks without interruption.
Based on data from 17 people who took the Breakroom Quiz between December 2024 and June 2026.

Is it stressful to work at Nvidia?

Some people feel stressed out here.
47% of people say they often feel stressed out at work.
Based on data from 17 people who took the Breakroom Quiz between December 2024 and June 2026.

Do people at Nvidia enjoy their jobs?

Most people enjoy their job.
100% of people report they enjoy their job.
Based on data from 15 people who took the Breakroom Quiz between December 2024 and June 2026.

Do people at Nvidia recommend working with their team?

Most people recommend working with their team.
76% of people report that they would recommend working with their immediate team to a friend.
Based on data from 17 people who took the Breakroom Quiz between December 2024 and June 2026.

Do people get enough training when they start at Nvidia?

Some people didn’t get enough training when they started.
38% of people report they didn’t get enough training when they started working here.
Based on data from 16 people who took the Breakroom Quiz between December 2024 and June 2026.

Do people get support to advance at Nvidia?

Most people are given support to advance their career here.
In the last year, 93% of people report being given support to advance their career here.
Based on data from 15 people who took the Breakroom Quiz between December 2024 and June 2026.

Do people think Nvidia’s headquarters understands what’s happening where they work?

Most people think headquarters understands what’s happening where they work.
67% of people think that this employer’s headquarters or owners have a good understanding of what’s really happening where they work.
Based on data from 15 people who took the Breakroom Quiz between December 2024 and June 2026.

Do workers feel well informed about how Nvidia is doing?

Most people feel well informed about how the company is doing.
94% of people feel that they are kept well informed about how the company is doing as a whole.
Based on data from 16 people who took the Breakroom Quiz between December 2024 and June 2026.
What are the most popular jobs at Nvidia?
What are the most popular categories at Nvidia?
Infographic showing various Ai Software Engineer job openings at Nvidia in the United States as of August 2026, with employment types broken down into 100% Full Time. Highlights an 84% Physical, 14% Hybrid, and 2% Remote job distribution.

Senior Systems Software Engineer, AI Stack and Performance - DGX Station

Nvidia Corporation

Santa Clara, CA • On-site

Full-time

Re-posted 8 days ago

Nvidia rating

9.6

Company rating: 9.6 out of 10

Based on 17 frontline employees who took The Breakroom Quiz

8th of 242 rated software companies

Job description

DGX Station (Galaxy) is NVIDIA's workstation-class AI computer-built on GB300 Blackwell GPUs with NVLink interconnect, delivering data-center-grade AI compute in a deskside form factor. DGX Station is shipped to OEM and OSV partners as a complete SW/FW GA release including firmware bundles, DGX BaseOS, GPU drivers, CUDA toolkit, DCGM, and DOCA/OFED. For DGX Station to deliver on its promise, AI applications like NemoClaw, LLM inference via NIM, Hermes agents, and deep learning frameworks must run production-ready out of the box-optimized for the multi-GPU, high-bandwidth architecture of this platform.
We are looking for a deeply technical systems software engineer who will own AI stack readiness on DGX Station. You will profile workloads, identify bottlenecks across GPU compute, NVLink, memory, and host interconnects, drive optimizations across the full stack-from GPU kernels through frameworks to applications-and work hands-on with framework, compiler, and GPU architecture teams to ensure DGX Station delivers best-in-class performance for real AI workloads in multi-user and multi-GPU configurations.
What you'll be doing:
  • AI Application Readiness: Own production readiness of AI applications on DGX Station-NemoClaw, Hermes agents, NIM microservices, and key customer workloads. Define "ready to ship" criteria, run validation, and close every gap between "it runs" and "it runs well" across single-GPU and multi-GPU configurations.
  • DL Framework Performance: Work cross functionally with different orgs to profile and optimize LLM and deep learning workloads (PyTorch, TensorFlow, JAX) across training and inference on the GB300 Blackwell multi-GPU architecture. Characterize performance across model sizes, batch sizes, precision modes (FP16, INT8, FP8), and GPU scaling (single-GPU vs. multi-GPU with NVLink) to establish benchmarks and identify regression.
  • System-Level Optimization: Identify bottlenecks in GPU compute, NVLink bandwidth, host memory, PCIe, and CPU-GPU communication. Implement or drive optimizations across the stack: kernel tuning, memory placement, NVLink utilization, data pipeline efficiency, and scheduling to increase throughput on DGX Station's multi-GPU topology.
  • Compiler & Kernel Collaboration: Work with NVIDIA's framework, compiler (TensorRT, NVCC, Triton), and GPU architecture teams to improve kernel fusion, graph execution, operator scheduling, and memory management for Blackwell GPUs. Translate DGX Station's platform-specific constraints and multi-GPU topology into actionable optimization requests for upstream teams.
  • Multi-User & Concurrency: Validate multi-user and concurrent workload scenarios-multiple users running simultaneous training jobs, inference serving alongside development, and resource isolation via MIG or time-slicing. Ensure DGX Station performs reliably as a shared workstation.
  • Stack Validation: Validate the full NVIDIA AI software stack on DGX Station: CUDA toolkit, cuDNN, TensorRT, NCCL, Triton Inference Server, DCGM, and DOCA/OFED. Ensure version compatibility, functional correctness, and performance parity with reference data center configurations.
  • Benchmarking & Regression: Build and maintain performance benchmarking infrastructure for DGX Station-automated regression tracking across key models (LLaMA, GPT, Stable Diffusion, Whisper), framework versions, and driver updates. Make performance data visible and actionable for GA release decisions.
  • Customer & Partner Alignment: Work with product management and OEM/OSV partners to understand target use cases (local LLM training and inference, agentic AI, multi-user research, RTX Pro workloads) and ensure DGX Station delivers compelling performance for each. Support customer deployment readiness and field critical issues.

What we need to see:
  • BS or MS or equivalent experience in Computer Science, Electrical Engineering, or related field.
  • 12+ years in systems software engineering with hands-on experience in AI/ML workload optimization, GPU performance analysis, or deep learning infrastructure.
  • Strong proficiency with deep learning frameworks-PyTorch, TensorFlow, or JAX-including internals: graph execution, operator dispatch, memory management, and custom kernel integration.
  • Experience profiling and optimizing GPU workloads using Nsight Systems, Nsight Compute, CUPTI, or equivalent. Ability to read GPU traces and translate observations into actionable optimizations.
  • Strong understanding of GPU architecture: compute units, memory hierarchy, NVLink, multi-GPU scaling, and how they impact AI workload performance.
  • Experience with inference optimization: quantization (INT8/FP8), model compilation (TensorRT, torch.compile), batching strategies, and serving frameworks.
  • Proficiency in C/C++, CUDA, and Python. Comfortable reading and modifying GPU kernels.

Ways to stand out from the crowd:
  • Experience optimizing LLM training or inference on multi-GPU NVIDIA systems (DGX, HGX, or multi-GPU workstations).
  • Contributions to open-source AI frameworks, CUDA libraries, or inference engines.
  • Experience with multi-GPU communication optimization-NCCL tuning, NVLink utilization, collective operations, and parallel training strategies.
  • Track record of collaborating with compiler and hardware architecture teams to drive kernel fusion, graph optimization, or hardware-specific performance improvements.
  • Experience shipping AI-powered products where application performance on specific hardware was a hard shipping requirement.

NVIDIA is considered one of the technology world's most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative and autonomous, we want to hear from you!
NVIDIA's invention of the GPU in 1999 fueled the growth of PC gaming, redefined modern computer graphics, and revolutionized parallel computing. GPU deep learning has since ignited a new chapter in computing, powering AI systems that can perceive and interpret the world. Today, NVIDIA is recognized as the AI computing company, and we're continuing to expand our teams with outstanding talent.
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 224,000 USD - 356,500 USD.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until July 30, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

What Nvidia employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

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About Nvidia

Sourced by ZipRecruiter

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It's a unique legacy of innovation that's fueled by great technology--and amazing people. Today, we're tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what's never been done before takes vision, innovation, and the world's best talent.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Santa Clara, CA, US

Year founded

1993

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