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Remote Nvidia Engineering Jobs (NOW HIRING)

Quantiphi, Inc.

Architect - Platform Engineer

Quantiphi is an award-winning, AI-First global digital engineering company that helps the world ... US East/Canada (Remote) Role Overview: We are looking for a highly skilled Architect - Platform ...

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Remote Nvidia Engineering information

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$57K

$137K

$197K

How much do remote nvidia engineering jobs pay per year?

As of Jul 23, 2026, the average yearly pay for remote nvidia engineering in the United States is $137,006.00, according to ZipRecruiter salary data. Most workers in this role earn between $121,500.00 and $151,500.00 per year, depending on experience, location, and employer.

What is a Remote Nvidia Engineer?

A Remote Nvidia Engineer is a professional who works for Nvidia, or with Nvidia technologies, from a location outside of a traditional office setting. These engineers may specialize in areas such as GPU development, AI research, software engineering, or hardware design, and they collaborate with teams virtually. Remote Nvidia Engineers use digital tools to communicate, manage projects, and contribute to cutting-edge technologies in graphics processing, artificial intelligence, and computing platforms. The remote aspect allows for flexible work arrangements and the ability to participate in global projects.

What are some common challenges faced by engineers working remotely for Nvidia, and how can they be overcome?

Remote engineers at Nvidia often encounter challenges related to communication across time zones, staying aligned with fast-paced project developments, and maintaining visibility within distributed teams. To overcome these, it's important to proactively engage in virtual meetings, leverage collaboration tools like Slack and Jira, and regularly update your team on progress. Building strong relationships with peers and seeking out mentorship opportunities can also help remote engineers stay connected and advance within the company.

What are the key skills and qualifications needed to thrive as a Remote Nvidia Engineer, and why are they important?

To excel as a Remote Nvidia Engineer, you typically need a strong background in computer engineering, programming (e.g., C++, Python), and experience with GPU architectures, often supported by a relevant degree. Familiarity with Nvidia tools like CUDA, cuDNN, and deep learning frameworks, as well as proficiency in remote collaboration platforms, are crucial. Strong problem-solving skills, self-motivation, and effective communication are vital soft skills for working independently and collaborating across distributed teams. These competencies ensure efficient development, troubleshooting, and innovation in Nvidia's complex, high-performance computing environments.

What is the difference between Remote Nvidia Engineering vs Remote Nvidia Data Scientist?

AspectRemote Nvidia EngineeringRemote Nvidia Data Scientist
Required CredentialsBachelor's in Engineering, Computer Science, or related field; experience with GPU programmingBachelor's or higher in Data Science, Statistics, or related; proficiency in machine learning and data analysis
Work EnvironmentDesign, develop, and optimize GPU hardware/software; collaborative teamsAnalyze large datasets, develop models, and generate insights; often cross-functional teams
Employer & Industry UsagePrimarily in hardware, AI, and high-performance computing sectorsPrimarily in AI, analytics, and research sectors

Remote Nvidia Engineering focuses on hardware and software development for GPUs, requiring engineering credentials and technical skills. Remote Nvidia Data Scientists analyze data and build models, requiring expertise in data science. Both roles are remote, but they serve different functions within Nvidia's ecosystem.

More about Remote Nvidia Engineering jobs
What cities are hiring for Remote Nvidia Engineering jobs? Cities with the most Remote Nvidia Engineering job openings:
What are the most commonly searched types of Nvidia Engineering jobs? The most popular types of Nvidia Engineering jobs are:
What states have the most Remote Nvidia Engineering jobs? States with the most job openings for Remote Nvidia Engineering jobs include:
What job categories do people searching Remote Nvidia Engineering jobs look for? The top searched job categories for Remote Nvidia Engineering jobs are:
Remote Nvidia Engineering jobs near you
Infographic showing various Remote Nvidia Engineering job openings in the United States as of July 2026, with employment types broken down into 93% Full Time, 4% Part Time, and 3% Contract. Highlights an 87% Physical, 4% Hybrid, and 9% Remote job distribution, with an average salary of $137,006 per year, or $65.9 per hour.
AI Infrastructure & Platform Operations Engineer (remote in the US)

AI Infrastructure & Platform Operations Engineer (remote in the US)

Mirantis

Remote

$110K - $144K/yr

Full-time

Posted 7 days ago

Job description

Company Description
Mirantis is the Kubernetes-native AI infrastructure company, enabling organizations to build and operate scalable, secure, and sovereign infrastructure for modern AI, machine learning, and data-intensive applications. By combining open source innovation with deep expertise in Kubernetes orchestration, Mirantis empowers platform engineering teams to deliver composable, production-ready developer platforms across any environment-on-premises, in the cloud, at the edge, or in sovereign data centers. As enterprises navigate the growing complexity of AI-driven workloads, Mirantis delivers the automation, GPU orchestration, and policy-driven control needed to manage infrastructure with confidence and agility. Committed to open standards and freedom from lock-in, Mirantis ensures that customers retain full control of their infrastructure strategy. https://www.mirantis.com/
Job Description
Our organization is establishing an Americas-based AI Infrastructure & Platform Operations unit dedicated to the management of expansive AI ecosystems utilizing NVIDIA GPU acceleration, high-speed interconnects, Kubernetes, and bleeding-edge platform frameworks.
This team maintains the reliability, efficiency, and architectural integrity of vital AI service platforms across a global datacenter footprint. Positioned at the nexus of core infrastructure and network engineering, you will sustain the high-performance environments essential for contemporary AI application suites.
This position offers the chance to engage with pioneering AI hardware while driving the development of automated operational capabilities via the k0rdent AI platform.
Responsibilities
  • Monitor, operate, and support production AI infrastructure platforms.
  • Investigate and resolve infrastructure, networking, hardware, and platform-related incidents.
  • Support NVIDIA GPU infrastructure and associated platform services.
  • Monitor and troubleshoot Kubernetes-based environments.
  • Investigate performance, availability, and reliability issues across infrastructure and platform components.
  • Collaborate with engineering teams, hardware vendors, Data Center personnel, and service delivery teams to resolve technical issues.
  • Participate in incident response, root cause analysis, and operational improvement activities.
  • Contribute to improvements in monitoring, observability, automation, and operational processes.
  • Maintain operational documentation, runbooks, and knowledge articles.

Qualifications
Required Experience
  • 3+ years of experience in infrastructure operations, platform operations, network operations, site reliability engineering, cloud operations, datacenter operations, or related technical roles.
  • Strong Linux administration and troubleshooting skills.
  • Good understanding of networking concepts and experience diagnosing infrastructure-related issues.
  • Working knowledge of Kubernetes in production environments.
  • Experience supporting production infrastructure and services.
  • Strong analytical and problem-solving skills.
  • Experience working within structured operational and incident management processes.
  • Excellent communication and collaboration skills.

Ability to work within a shift-based operational environment.
Preferred Experience
Experience in one or more of the following areas is highly desirable:
  • NVIDIA GPU infrastructure and accelerated computing platforms.
  • InfiniBand networking and NVIDIA UFM.
  • Kubernetes platform operations.
  • AI infrastructure or HPC environments.
  • Site Reliability Engineering (SRE) or Platform Engineering.
  • Observability platforms such as Grafana, Prometheus, ELK, or OpenTelemetry.
  • Infrastructure automation technologies and Infrastructure-as-Code practices.
  • Large-scale distributed systems and production platforms.

Why Join Us?
  • Work with some of the most advanced AI infrastructure environments in production today.
  • Gain exposure to NVIDIA GPU technologies, Kubernetes platforms, and high-performance networking environments.
  • Help define how next-generation AI infrastructure is operated and supported.
  • Be part of a team shaping the future of AI-powered operations through k0rdent AI.
  • Join a growing organisation investing heavily in AI infrastructure and platform services.

Additional Information
What does Mirantis offer you?
  • Work with an established Silicon Valley leader in the cloud infrastructure industry;
  • Work with exceptionally passionate, talented and engaging colleagues, helping Fortune 500 and Global 2000 customers implement next-generation cloud technologies;
  • Be a part of cutting-edge, open-source innovation;
  • Thrive in the high-energy environment of a young company where openness, collaboration, risk-taking, and continuous growth are valued;
  • Professional development and training;
  • Attend conferences and working groups;
  • Company outings, happy hours, hackathons, and tech talks;
  • Receive a competitive compensation package with a strong benefits plan.

We are a Leader for Container Management in G2 (#2 after AWS)!

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