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Remote Nvidia Deep Learning Jobs (NOW HIRING)

$104K - $142K/yr

NVIDIA's deep learning platforms have made major impact to various fields is broadly used across leading academic institutions, start-ups, and industry, including the world's largest Internet ...

We are now looking for a Senior Deep Learning Hardware Modeling Architect ... NVIDIA seeks a Senior DL Hardware Modeling Architect to join our group of pioneers who are pushing ...

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than ... Profiles should be comfortable in a dynamic environment with experience in Deep Learning, LLMs, and ...

More recently, GPU deep learning ignited modern AI - the next era of computing. NVIDIA is a "learning machine" that constantly evolves by adapting to new opportunities that are hard to solve, that ...

Senior DL Compiler Engineer -CUDA Tile

OR · On-site +1

$122K - $161K/yr

NVIDIA GPUs are at the center of the deep learning revolution and continue to enable breakthroughs in generative AI, large language models, recommendation systems, speech recognition, image ...

Position Summary As a Senior Deep Learning Engineer on the Football Modeling side, you'll work ... Remote working environment * A flexible, unlimited time off policy * Generous paid holiday schedule ...

... NVIDIA's invention of the GPU 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited ...

... NVIDIA accelerated serving stack. What we need to see: * Bachelor's of Master's degree in Computer Science or equivalent experience. * 8+ years of industry experience in Deep Learning frameworks ...

Collaborating closely with other engineers at NVIDIA across deep learning frameworks, libraries, kernels, and GPU arch teams * Contributing to open source communities like FlashInfer, vLLM, and ...

Showing results 21-40

Remote Nvidia Deep Learning information

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$11K

$83.9K

$140K

How much do remote nvidia deep learning jobs pay per year?

As of Aug 21, 2026, the average yearly pay for remote nvidia deep learning in the United States is $83,885.00, according to ZipRecruiter salary data. Most workers in this role earn between $72,000.00 and $139,000.00 per year, depending on experience, location, and employer.

What is the difference between Remote Nvidia Deep Learning vs Remote Machine Learning Engineer?

AspectRemote Nvidia Deep LearningRemote Machine Learning Engineer
Required CredentialsDeep learning certifications, Nvidia GPU expertise, programming skills in Python and CUDAMachine learning certifications, Python, data analysis, model deployment skills
Work EnvironmentRemote, GPU-intensive tasks, AI research, model trainingRemote, data processing, model development, deployment
Industry UsageAI research labs, tech companies, autonomous vehiclesTech firms, finance, healthcare, e-commerce

Remote Nvidia Deep Learning focuses on developing AI models using Nvidia GPUs and CUDA, often in research or AI-specific roles. Remote Machine Learning Engineers work on building and deploying machine learning models across various industries. While both roles require programming and data skills, Nvidia Deep Learning emphasizes GPU expertise and AI research, whereas Machine Learning Engineers focus on broader model deployment and application.

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The most popular types of Nvidia Deep Learning jobs are:

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Infographic showing various Remote Nvidia Deep Learning job openings in the United States as of August 2026, with employment types broken down into 10% Internship, 60% Full Time, and 30% Contract. Highlights an 100% Remote job distribution, with an average salary of $83,885 per year, or $40.3 per hour.

Senior Platform Engineer, Network Infrastructure - DGX Cloud

Nvidia

On-site, Remote

$104K - $142K/yr

Full-time

Re-posted 6 days ago


Nvidia rating

9.6

Company rating: 9.6 out of 10

Based on 17 frontline employees who took The Breakroom Quiz

7th of 245 rated software companies


Job description

Cloud Foundations Reliability (CFR) is part of NVIDIA's Global Network Infrastructure (GNI) organization. We deploy, integrate, and operate the Kubernetes-based platform and shared services used to provision, monitor, and operate NVIDIA's global network across data centers, colocation facilities, and cloud environments. The team owns the architecture and lifecycle of this platform, including cluster provisioning and upgrades, GitOps delivery, observability, capacity, and service enablement. We build software and automation to standardize how network platforms and services are deployed, scaled, and managed across environments.

We are looking for a hands-on senior engineer to own the lifecycle and automation of the Kubernetes platform supporting GNI network systems. You will also provide production support for network services running on the platform, partnering with their engineering owners when issues or changes cross the platform boundary. You will take complex problems from design through production and remain accountable for the outcome. You will bring deep Kubernetes expertise and help establish consistent engineering practices across the US and Bangalore teams. This is a senior individual contributor role with end-to-end ownership and production responsibility.

What You'll Be Doing:

  • Design, build, and operate the Kubernetes platform that powers GNI network automation, telemetry, and operations across data center, colocation, and cloud environments.

  • Own the lifecycle management for GNI Kubernetes environments, including cluster onboarding, upgrades, capacity, availability, and recovery.

  • Develop production-quality software and automation for cluster provisioning, validation, upgrades, remediation, and safe multi-cluster delivery through GitOps.

  • Provide production support for network services hosted on the platform, working with Network Automation and service teams that retain ownership of application architecture, code, and features.

  • Diagnose complex Kubernetes platform and hosted-service failures involving control-plane health, cluster networking, storage, scheduling, workload placement, and multi-cluster dependencies. Drive issues from initial signal through verified resolution.

  • Define production-readiness and observability standards for the platform and hosted network services, including health signals, capacity, alerts, runbooks, and recovery.

  • Participate in CFR's production on-call rotation, including scheduled after-hours and weekend coverage. Lead incident response and recovery, then drive corrective actions to completion.

What We Need to See:

  • Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent experience.

  • 8+ years of experience building or operating production Kubernetes platforms, network infrastructure, or distributed systems.

  • Deep experience with Kubernetes at scale, including cluster lifecycle, upgrades, networking, storage, and recovery.

  • Proficiency in at least one general-purpose programming language, such as Go or Python.

  • Experience with GitOps, infrastructure as code, CI/CD, and automated production delivery.

  • Experience deploying and supporting network automation or telemetry services on Kubernetes.

  • Experience with production on-call, incident response, root-cause analysis, and driving corrective actions to completion.

Ways to Stand Out From the Crowd:

  • Strong knowledge of IP routing, data center fabrics, and cloud networking is a great plus.

  • Experience designing and operating large, multi-region Kubernetes fleets, including fleet-wide upgrades and recovery.

  • Hands-on experience with Cluster API (CAPI) and Metal3 for bare-metal provisioning, cluster lifecycle, machine remediation, and upgrades.

  • Experience building Kubernetes controllers or operators in Go using custom resources and reconciliation patterns.Experience designing or operating network automation and telemetry services on Kubernetes at global scale.

  • Contributions to Cluster API, Metal3, or other open-source Kubernetes infrastructure projects.

NVIDIA's deep learning platforms have made major impact to various fields is broadly used across leading academic institutions, start-ups, and industry, including the world's largest Internet companies. We need passionate, hard-working and creative people to help us take on more of these unique opportunities in deep learning cloud solutions. NVIDIA is widely considered to be one of the technology world's most desirable employers. We have some of the most forward-thinking and hard-working people in the world working for us. Are you creative and autonomous? Do you love a challenge? If so, we want to hear from you.

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 176,000 USD - 276,000 USD for Level 4, and 208,000 USD - 333,500 USD for Level 5.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until August 21, 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.

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Benefits

Hours and flexibility

Workplace

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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