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Nvidia Hardware Engineer Jobs in Seattle, WA (NOW HIRING)

Senior LLVM Compiler Engineer

Redmond, WA · On-site

$117K - $160K/yr

... NVIDIA hardware and software requirements into upstream‑viable compiler solutions • Help shape NVIDIA's long‑term open‑source LLVM strategy, balancing ecosystem health with NVIDIA's platform ...

At NVIDIA, we believe that inference will be driving increasing amount of compute, and as the hardware becomes more capable, it is crucial to make it easy for users to get the best performance as ...

Senior LLVM Compiler Engineer

Redmond, WA · On-site

$117K - $160K/yr

Partner with architecture, performance, and product teams to translate NVIDIA hardware and software ... D. in Computer Science, Computer Engineering, or related field (or equivalent experience) * 6+ ...

NVIDIA is searching for a highly motivated, creative engineer to join the GPU Software team. As a GPU/SOC system software engineer, you will work with a team of very dedicated software and hardware ...

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Nvidia Hardware Engineer information

See Seattle, WA salary details

$58K

$166.4K

$223.6K

How much do nvidia hardware engineer jobs pay per year?

As of Aug 3, 2026, the average yearly pay for nvidia hardware engineer in Seattle, WA is $166,414.00, according to ZipRecruiter salary data. Most workers in this role earn between $140,500.00 and $185,500.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an Nvidia hardware engineer?

To thrive as an Nvidia Hardware Engineer, you need a strong background in electrical engineering, digital and analog circuit design, and familiarity with ASIC/FPGA development, typically demonstrated through a relevant degree and experience. Expertise with industry-standard tools like Cadence, Synopsys, and scripting languages, as well as knowledge of hardware validation methods, is frequently required. Strong problem-solving abilities, teamwork, and effective communication help engineers navigate complex projects and work across multidisciplinary groups. These skills and qualities are critical for designing innovative, high-performance hardware components and ensuring their successful integration into Nvidia’s advanced technologies.

What does an Nvidia hardware engineer do?

A typical day for an Nvidia Hardware Engineer involves designing, simulating, and testing hardware components, often working closely with software, verification, and product teams to ensure designs meet performance and reliability standards. The role includes reviewing schematics, running validation tests, analyzing data, and addressing technical challenges as they arise. Engineers regularly participate in cross-functional meetings to align on project goals, share updates, and troubleshoot issues collaboratively. This collaborative environment ensures that new Nvidia products are developed efficiently and meet the industry’s demanding standards, providing engineers with significant opportunities for learning and professional growth.

What is an Nvidia hardware engineer?

An Nvidia Hardware Engineer is responsible for designing, developing, and optimizing cutting-edge hardware components such as GPUs, AI accelerators, and high-performance computing chips. They work on circuit design, system architecture, validation, and performance optimization to ensure Nvidia's products meet industry standards. These engineers collaborate with software teams to enhance hardware-software integration and improve efficiency. The role requires expertise in areas like VLSI design, FPGA/ASIC development, and power management. Strong problem-solving skills and a background in electrical or computer engineering are essential.

What are the most commonly searched types of Nvidia Hardware Engineer jobs in Seattle, WA? The most popular types of Nvidia Hardware Engineer jobs in Seattle, WA are:
What are popular job titles related to Nvidia Hardware Engineer jobs in Seattle, WA? For Nvidia Hardware Engineer jobs in Seattle, WA, the most frequently searched job titles are:
What job categories do people searching Nvidia Hardware Engineer jobs in Seattle, WA look for? The top searched job categories for Nvidia Hardware Engineer jobs in Seattle, WA are:
Infographic showing various Nvidia Hardware Engineer job openings in Seattle, WA as of July 2026, with employment types broken down into 92% Full Time, 4% Part Time, and 4% Contract. Highlights an 89% Physical, 4% Hybrid, and 7% Remote job distribution, with an average salary of $166,414 per year, or $80 per hour.

Senior Systems Software Engineer, Kubernetes Node Lifecycle - DGX Cloud

Nvidia

Seattle, WA • On-site

$68.25 - $88.75/hr

Full-time

Re-posted 23 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 241 rated software companies


Job description

At NVIDIA, the DGX Cloud division merges fresh hardware and software innovations to offer leading accelerated computing solutions for the most challenging AI workloads worldwide. Our team of skilled engineers is committed to addressing major global issues, consistently advancing technology, and making a difference in millions of lives around the world!

We are looking for a Senior Systems Software Engineer with strong experience in Kubernetes node engineering, OS image packaging, and cloud infrastructure. The ideal candidate will possess deep hyperscaler-level knowledge across the entire node lifecycle. This covers CAPI providers, bring-your-own-node onboarding, OS image build pipelines, packaging, and nodepool management. They must have the technical depth needed to maintain cluster reliability at frontier AI scale. In this vital role, you will manage the node layer within NVIDIA Kubernetes Engine (NKE). Your work will ensure it scales to fulfill DGX Cloud's two main goals: supporting internal researchers and enabling NCPs. Are you prepared to innovate?

What you'll be doing:

  • Direct the building and refinement of CAPI providers for NVIDIA Kubernetes Engine, maintaining steady, consistent, and scalable node provisioning across DGX Cloud and NCP environments.

  • Develop and maintain bring-your-own-node workflows that allow customers to integrate different NVIDIA hardware into NKE clusters while ensuring high operational consistency.

  • Coordinate OS image generation, packaging, deployment, and update processes for NKE nodes. Ensure images are fine-tuned for NVIDIA GPU workloads and satisfy enterprise- and cloud-grade security and compliance criteria.

  • Develop and sustain node image hardening pipelines, incorporating CIS benchmarks, automated CVE remediation, and promotion gates connected to security posture.

  • Develop and maintain automated test suites for node images. These tests verify accuracy across Kubernetes versions and NVIDIA hardware configurations. This process occurs prior to production deployment and facilitates continuous validation through modern CI/CD pipelines.

  • Handle nodepool lifecycle at scale, including provisioning, upgrades, drain and cordon workflows, and seamless node replacement across very large clusters with diverse NVIDIA hardware.

  • Examine, resolve, and determine underlying causes of node-layer faults in production NKE clusters, such as those involving image configuration, driver packaging, kubelet operation, and hardware activation, and review and optimize the node layer in real-world high-scale scenarios.

  • Partner with upstream communities including Cluster API, Kubernetes, and CNCF projects to establish node provisioning and lifecycle standards in accordance with NKE requirements. Communicate your progress and findings at internal and external gatherings such as KubeCon and GTC.

What we need to see:

  • 8 years of experience with a background in systems software, cloud infrastructure, or Kubernetes node engineering.

  • Bachelor's or Master's degree in Engineering (Electrical, Computer Engineering, Computer Science) or equivalent experience.

  • Deep expertise in Cluster API (CAPI), including provider development and full machine lifecycle from provisioning to deletion.

  • Extensive experience with OS image build pipelines, node image packaging, and delivery systems for Kubernetes nodes (for example image-builder, containerd, cloud-init, packer).

  • Practical experience with bring-your-own-node models and integrating diverse hardware into live Kubernetes environments, including large-scale nodepool lifecycle management and upgrades.

  • Strong understanding of kubelet configuration, node bootstrap, and the Kubernetes node registration lifecycle.

  • Experience with node image security, including vulnerability scanning, patch automation, and compliance gating as part of image build pipelines.

  • Proficiency in Golang and/or Python, and hands-on experience with at least one major public cloud provider (GCP, AWS, Azure, OCI or equivalent).

Ways to stand out from the crowd:

  • Direct experience building or maintaining node image pipelines for a hyperscaler Kubernetes distribution (GKE, EKS, AKS, OKE, or equivalent).

  • Experience with supply chain security and hardening for node images, including image signing, provenance attestation, SBOM generation, CIS benchmark consistency, and automated CVE remediation.

  • Experience with automated node provisioning and optimal sizing at scale (for example Karpenter, GKE NAP or similar) and how these interact with GPU workload scheduling.

  • Strong operational experience working with immutable OS image distributions (such as Flatcar, Bottlerocket, Azure Linux) and debugging node-layer failures in large Kubernetes clusters.

  • Proven background of upstream contributions to Cluster API, Kubernetes or related CNCF projects, combined with excellent communication and interpersonal abilities.

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until June 14, 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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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