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Dgx Jobs (NOW HIRING)

Nvidia

OR · On-site

$134K - $180K/yr

NVIDIA DGX Cloud is scaling GPU infrastructure across internal, partner, and cloud environments. We are looking for Principal Software Engineers to help shape the technical direction for production ...

Nvidia

OR · On-site

$122K - $161K/yr

NVIDIA DGX Cloud is building and operating large-scale GPU infrastructure for AI research and production workloads. We are looking for Senior Software Engineers to help build the automation, tooling ...

Nvidia

OR · On-site

$122K - $161K/yr

NVIDIA DGX Cloud is building and operating large-scale GPU infrastructure for AI research and production workloads. We are looking for Senior Software Engineers to help build the automation, tooling ...

Nvidia

OR · On-site

$122K - $161K/yr

NVIDIA DGX Cloud is building and operating large-scale GPU infrastructure for AI research and production workloads. We are looking for Senior Software Engineers to help build the automation, tooling ...

Nvidia

Principal Software Engineer - DGX Cloud

Seattle, WA

$153K - $206K/yr

As a Principal Engineer in DGX Cloud, you will be at the pinnacle of technical leadership. You will directly craft the platform that fuels the future of AI and cloud computing. What you'll be doing:

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$37K

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How much do dgx jobs pay per year?

As of Jun 10, 2026, the average yearly pay for dgx in the United States is $78,442.00, according to ZipRecruiter salary data. Most workers in this role earn between $64,000.00 and $93,500.00 per year, depending on experience, location, and employer.

What are DGX jobs?

DGX jobs refer to tasks or workloads that are executed on NVIDIA DGX systems, which are specialized high-performance computing platforms designed for AI and deep learning applications. These jobs often involve training large machine learning models, running complex simulations, or processing vast amounts of data. DGX systems are equipped with powerful GPUs and optimized software to accelerate computation, making them popular in research, data science, and enterprise AI development. Users typically submit DGX jobs through job schedulers or containerized environments to efficiently utilize the hardware resources.

What is the difference between Dgx vs X-ray Technician?

AspectDgxX-ray Technician
Required CredentialsCertification in diagnostic imaging, radiologic technology licenseCertification in radiologic technology, state license
Work EnvironmentHospitals, imaging centers, clinicsHospitals, outpatient clinics, diagnostic labs
Industry UsageCommonly used in diagnostic imaging and radiologyWidely used in medical imaging and diagnostics
Job FocusOperating CT scanners and advanced imaging equipmentPerforming X-ray procedures and basic imaging

While both Dgx and X-ray Technicians work in medical imaging, Dgx specialists typically operate advanced diagnostic equipment like CT scanners, requiring specialized training. X-ray Technicians focus on performing X-ray procedures, often with different certification requirements. Understanding these differences helps in choosing the right career path or job search focus.

What are the key skills and qualifications needed to thrive as a DGX (NVIDIA DGX System) Specialist, and why are they important?

To thrive as an NVIDIA DGX Specialist, you need a strong background in computer science, deep learning frameworks, and system administration, often supported by a relevant degree and experience with GPU-accelerated computing. Familiarity with DGX software stack, Linux environments, containerization tools (like Docker), and NVIDIA CUDA is typically required, along with certifications such as NVIDIA Certified Systems Engineer. Strong problem-solving skills, attention to detail, and effective communication set standout professionals apart in this field. These skills ensure optimal system performance, support advanced AI workloads, and facilitate collaboration with data science and IT teams.

What are some common challenges faced by professionals working with NVIDIA DGX systems, and how can they be addressed?

Professionals working with NVIDIA DGX systems often encounter challenges such as managing large-scale data workflows, optimizing GPU utilization, and troubleshooting hardware or software integration issues. Staying updated with the latest software drivers and leveraging NVIDIA’s support resources can help address these obstacles. Collaborating closely with data scientists, IT teams, and system administrators is crucial for smooth operations and maximizing system performance. Regular training and hands-on practice with DGX tools can also enhance efficiency and problem-solving abilities.
More about Dgx jobs
What cities are hiring for Dgx jobs? Cities with the most Dgx job openings:
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What job categories do people searching Dgx jobs look for? The top searched job categories for Dgx jobs are:
Dgx jobs near you
Infographic showing various Dgx job openings in the United States as of June 2026, with employment types broken down into 99% Full Time, and 1% Contract. Highlights an 87% Physical, 5% Hybrid, and 8% Remote job distribution, with an average salary of $78,442 per year, or $37.7 per hour.
Senior Technical Product Manager - DGX Enterprise Infrastructure and Cloud-Native Operations

Senior Technical Product Manager - DGX Enterprise Infrastructure and Cloud-Native Operations

NVIDIA

Santa Clara, CA • On-site

$148K - $196K/yr

Full-time

Posted 28 days ago

Job description

Job Summary:
NVIDIA is seeking a world-class Senior Product Manager to architect for the operational future of Enterprise AI. In this role, you will define the vision and lead the development of products that transform DGX hardware into a high-availability, self-healing AI Factory.
Responsibilities:
• Set the vision for the Enterprise Operational Gold Standard.
• Define how the world’s most sophisticated companies deploy, manage, and scale their Enterprise AI Factories.
• Productize the On-Prem Lifecycle: Define the "Day 0 through Day 2" experience for DGX SuperPODs.
• Lead the development of products that handle everything from bare-metal provisioning and network fabric configuration to automated "one-click" firmware rollouts.
• Develop a definitive telemetry and diagnostic suite.
• When a job slows down in a private data center, your framework should provide the "one-click" answer—isolating a thermal throttle, a degraded InfiniBand rail, or a cabling fault instantly.
• Lead the integration of DGX systems into the cloud-native ecosystem.
• Ensure that enterprise-grade features like GPU partitioning (MIG), multi-node scaling, and niche scheduling are declarative and seamless.
• You aren't just building scripts; but building APIs and Services.
• Your goal is to eliminate "management snowflakes," ensuring that every enterprise DGX deployment is standardized, repeatable, and resilient.
• Move the needle from reactive maintenance to self-healing infrastructure.
• Thoughtfully define the features for automated health checks that keep the fleet at peak performance without manual intervention.
Qualifications:
Required:
• 12+ years demonstrated ability in Product Management, with specific experience around on-premise infrastructure, private cloud, or large-scale systems management.
• Bachelors Degree in Computer Science or related field or equivalent experience.
• A track record of turning complex hardware operations into software-defined workflows.
• Expert-level understanding of Kubernetes operators, container orchestration, and how to translate physical hardware constraints into declarative code.
• Experience managing large-scale Linux fleets in air-gapped or restricted enterprise environments.
• Deep familiarity with data center networking (InfiniBand/Ethernet), storage architectures, and the firmware-to-OS handshake.
• Ability to define the NVIDIA Datacenter Experience and transition into formal people management as the team expands.
Preferred:
• Experience with infrastructure-as-code (Ansible, Terraform, Pulumi) in a bare-metal context.
• Vision for using AI to manage AI—applying telemetry and machine learning to predict and prevent infrastructure failures.
• Belief that the 'Gold Standard' isn't just about speed—it's about the reliability and simplicity of the Automated Pit Crew.
Company:
NVIDIA is a computing platform company operating at the intersection of graphics, HPC, and AI. Founded in 1993, the company is headquartered in Santa Clara, USA, with a team of 10001+ employees. The company is currently Late Stage.
Nvidia logo

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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