Systems Engineer Jobs at NVIDIA with Visa Sponsorship
Systems Engineer jobs at NVIDIA sit at the intersection of hardware architecture, software integration, and large-scale infrastructure deployment. NVIDIA has a consistent track record of sponsoring international engineers across H-1B visa, E-3 visa, and employment-based Green Card pathways, making it a realistic target for qualified candidates who need work authorization.
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Get Access To All JobsINTRODUCTION
Systems Engineering is an engineering discipline focused on building, automating, and operating the platforms and tooling that deliver large-scale production systems with high efficiency, reliability, and velocity. It combines software and systems engineering practices across infrastructure automation, containerized platforms, storage, telemetry, and observability. Systems engineers are highly specialized and possess expertise across domains such as Kubernetes and container orchestration, infrastructure-as-code, CI/CD, storage systems, monitoring, and analytical troubleshooting. Their responsibilities center on deploying and operating reliable, automated platforms and on building the tools and services that keep storage and data infrastructure healthy and performant.
Our team at NVIDIA ensures that our internal and external facing GPU cloud services are deployed reliably, observable end-to-end, and continuously improved through automation. We enable developers to ship changes safely through repeatable CI/CD pipelines and Kubernetes-based deployments while keeping an eye on capacity, latency, and performance. A core part of this work is an SRE mindset: eliminating manual toil through automation, building self-service tooling, and growing the efficiency of production systems. We use a breadth of tools and approaches to tackle a broad spectrum of problems, and practices such as blameless postmortems, proactive identification of failure modes, and iterative improvement are key to product quality and to an interesting, dynamic day-to-day. Our culture of diversity, intellectual curiosity, problem-solving, and openness is important to our success. Our organization brings together people with a wide variety of backgrounds, experiences, and perspectives. We encourage them to collaborate, think big, and take risks in a blame-free environment. We promote self-direction to work on meaningful projects while striving to build an environment that provides the support and mentorship needed to learn and grow.
What You Will Be Doing:
- Design, deploy, and operate solutions on Kubernetes for large-scale storage and data platforms, including the manifests, Helm charts, and operators that run them.
- Build tools, services, and automation that improve the lifecycle of storage and data systems – from provisioning and configuration through deployment, scaling, and day-2 operations.
- Develop and operate telemetry and observability for production systems – metrics, logging, tracing, dashboards, and alerting – so that system health, availability, and latency are measurable and actionable.
- Apply strong analytical troubleshooting skills to diagnose and resolve complex issues across distributed, containerized infrastructure.
- Work closely with peers and partner teams to improve the lifecycle of services, from inception and design through deployment, operation, and refinement.
- Scale systems sustainably through automation, infrastructure-as-code, and CI/CD, and evolve systems by pushing for changes that improve reliability and velocity.
- Support services before they go live through activities such as deployment automation, capacity planning, and launch and readiness reviews.
- Practice sustainable incident response and postmortems, and participate in an on-call rotation to support production systems.
What We Need To See:
- BS degree (or equivalent experience) in Computer Science or related technical field involving coding.
- 12+ years of practical experience.
- Hands-on experience with Kubernetes – deploying, configuring, and operating workloads and solutions on Kubernetes in production.
- Experience building tools and services for storage, data, or platform infrastructure, with solid software design fundamentals (algorithms, data structures, complexity analysis) on large-scale Linux-based systems.
- Experience building and operating telemetry and observability using tools such as Prometheus, InfluxDB, Grafana, and the Elastic stack.
- Strong analytical troubleshooting skills with a systematic, root-cause-driven approach to identifying and resolving complex problems.
- Proficiency in one or more of the following: Python, Go, or Java.
- Good knowledge of infrastructure configuration management and infrastructure-as-code tools such as Ansible, Chef, Puppet, ArgoCD, Git Pipelines, and Terraform.
Ways to Stand Out from the Crowd:
- Customer-first mindset with a focus on customer satisfaction and a passion for ensuring customer success.
- Experience with Git, code review, pipelines, and CI/CD. Experience using or running large private and public cloud systems based on Kubernetes, OpenStack, and Docker.
- Interest in crafting, analyzing, and fixing large-scale distributed systems, with strong debugging skills and a systematic problem-solving approach.
- Experience designing storage- or data-focused tooling and automating their operations at scale.
- Thrive in collaborative environments and enjoy working with various teams, and are flexible in adapting to different working styles.
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 208,000 USD - 333,500 USD for Level 5, and 256,000 USD - 414,000 USD for Level 6.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until June 12, 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.
INTRODUCTION
Systems Engineering is an engineering discipline focused on building, automating, and operating the platforms and tooling that deliver large-scale production systems with high efficiency, reliability, and velocity. It combines software and systems engineering practices across infrastructure automation, containerized platforms, storage, telemetry, and observability. Systems engineers are highly specialized and possess expertise across domains such as Kubernetes and container orchestration, infrastructure-as-code, CI/CD, storage systems, monitoring, and analytical troubleshooting. Their responsibilities center on deploying and operating reliable, automated platforms and on building the tools and services that keep storage and data infrastructure healthy and performant.
Our team at NVIDIA ensures that our internal and external facing GPU cloud services are deployed reliably, observable end-to-end, and continuously improved through automation. We enable developers to ship changes safely through repeatable CI/CD pipelines and Kubernetes-based deployments while keeping an eye on capacity, latency, and performance. A core part of this work is an SRE mindset: eliminating manual toil through automation, building self-service tooling, and growing the efficiency of production systems. We use a breadth of tools and approaches to tackle a broad spectrum of problems, and practices such as blameless postmortems, proactive identification of failure modes, and iterative improvement are key to product quality and to an interesting, dynamic day-to-day. Our culture of diversity, intellectual curiosity, problem-solving, and openness is important to our success. Our organization brings together people with a wide variety of backgrounds, experiences, and perspectives. We encourage them to collaborate, think big, and take risks in a blame-free environment. We promote self-direction to work on meaningful projects while striving to build an environment that provides the support and mentorship needed to learn and grow.
What You Will Be Doing:
- Design, deploy, and operate solutions on Kubernetes for large-scale storage and data platforms, including the manifests, Helm charts, and operators that run them.
- Build tools, services, and automation that improve the lifecycle of storage and data systems – from provisioning and configuration through deployment, scaling, and day-2 operations.
- Develop and operate telemetry and observability for production systems – metrics, logging, tracing, dashboards, and alerting – so that system health, availability, and latency are measurable and actionable.
- Apply strong analytical troubleshooting skills to diagnose and resolve complex issues across distributed, containerized infrastructure.
- Work closely with peers and partner teams to improve the lifecycle of services, from inception and design through deployment, operation, and refinement.
- Scale systems sustainably through automation, infrastructure-as-code, and CI/CD, and evolve systems by pushing for changes that improve reliability and velocity.
- Support services before they go live through activities such as deployment automation, capacity planning, and launch and readiness reviews.
- Practice sustainable incident response and postmortems, and participate in an on-call rotation to support production systems.
What We Need To See:
- BS degree (or equivalent experience) in Computer Science or related technical field involving coding.
- 12+ years of practical experience.
- Hands-on experience with Kubernetes – deploying, configuring, and operating workloads and solutions on Kubernetes in production.
- Experience building tools and services for storage, data, or platform infrastructure, with solid software design fundamentals (algorithms, data structures, complexity analysis) on large-scale Linux-based systems.
- Experience building and operating telemetry and observability using tools such as Prometheus, InfluxDB, Grafana, and the Elastic stack.
- Strong analytical troubleshooting skills with a systematic, root-cause-driven approach to identifying and resolving complex problems.
- Proficiency in one or more of the following: Python, Go, or Java.
- Good knowledge of infrastructure configuration management and infrastructure-as-code tools such as Ansible, Chef, Puppet, ArgoCD, Git Pipelines, and Terraform.
Ways to Stand Out from the Crowd:
- Customer-first mindset with a focus on customer satisfaction and a passion for ensuring customer success.
- Experience with Git, code review, pipelines, and CI/CD. Experience using or running large private and public cloud systems based on Kubernetes, OpenStack, and Docker.
- Interest in crafting, analyzing, and fixing large-scale distributed systems, with strong debugging skills and a systematic problem-solving approach.
- Experience designing storage- or data-focused tooling and automating their operations at scale.
- Thrive in collaborative environments and enjoy working with various teams, and are flexible in adapting to different working styles.
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 208,000 USD - 333,500 USD for Level 5, and 256,000 USD - 414,000 USD for Level 6.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until June 12, 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.
See all 96+ Systems Engineer Jobs at NVIDIA
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Get Access To All JobsTips for Finding Systems Engineer Jobs at NVIDIA
Tailor your resume to NVIDIA's technical stack
NVIDIA's Systems Engineer postings consistently emphasize GPU architecture, CUDA, high-speed networking, and data center infrastructure. Align your resume to those specific technologies before applying. Generic systems engineering CVs rarely clear NVIDIA's initial screening.
Target teams with active LCA filings
Search DOL's OFLC disclosure database for NVIDIA's certified Labor Condition Applications under the Systems Engineer job title. Teams with recent LCA activity have cleared internal approvals to sponsor, making them far more receptive to candidates who need visa support.
Raise sponsorship early in recruiter conversations
NVIDIA's recruiting process moves quickly from phone screen to technical rounds. Confirm the role is open to sponsored candidates before investing in case study prep or take-home assessments. This avoids late-stage surprises after weeks of interviews.
Understand how NVIDIA structures H-1B cap timing
If you're outside cap-exempt status, USCIS's April 1 filing window and October 1 start date govern when you can begin work. Align your offer negotiation with NVIDIA's HR team around that cycle so your expected start date is realistic for both sides.
Build credentials that demonstrate specialty occupation standing
USCIS evaluates whether a Systems Engineer role genuinely requires a specialized degree. Certifications in NVIDIA-relevant domains like data center networking, GPU computing, or systems architecture strengthen the specialty occupation argument in your I-129 petition.
Use Migrate Mate to filter verified NVIDIA openings
Not all NVIDIA Systems Engineer postings explicitly state visa sponsorship availability. Use Migrate Mate to filter for roles at NVIDIA that are confirmed open to sponsored candidates, so you're applying where your visa situation won't disqualify you late in the process.
Frequently Asked Questions
Does NVIDIA sponsor H-1B visas for Systems Engineers?
Yes. NVIDIA sponsors H-1B visas for Systems Engineer roles and has done so consistently across its hardware, networking, and data center infrastructure teams. The process follows the standard H-1B cap lottery cycle unless you qualify for a cap-exempt pathway. NVIDIA's legal and HR teams handle the I-129 filing, but confirming sponsorship availability upfront with your recruiter is essential since not every open role is approved for sponsorship.
How do I apply for Systems Engineer jobs at NVIDIA?
Apply directly through NVIDIA's careers portal, where Systems Engineer roles are listed by business unit, including data center, networking, and embedded systems teams. Tailor your application to the specific technical requirements in the job description rather than submitting a generic resume. If you need visa sponsorship, confirm that with the recruiter at the first screening call before progressing through NVIDIA's multi-stage technical interview process.
Which visa types does NVIDIA use to sponsor Systems Engineers?
NVIDIA sponsors Systems Engineers on H-1B visas, E-3 visas for Australian citizens, and employment-based Green Cards through the EB-2 and EB-3 categories. The right pathway depends on your nationality, your current immigration status, and how long you've been in the U.S. NVIDIA's immigration counsel typically advises on which petition type fits your situation after you receive an offer.
What qualifications does NVIDIA expect for sponsored Systems Engineer roles?
Most Systems Engineer roles at NVIDIA require a bachelor's degree or higher in electrical engineering, computer engineering, or computer science, with hands-on experience in areas like GPU systems, high-speed interconnects, or data center infrastructure. This matters beyond just hiring: USCIS requires the role to qualify as a specialty occupation for H-1B purposes, so NVIDIA's job descriptions are typically written to reflect that degree-specific requirement clearly.
How do I find Systems Engineer roles at NVIDIA that are open to visa sponsorship?
Not every Systems Engineer posting at NVIDIA explicitly flags visa sponsorship eligibility, which makes filtering time-consuming. Migrate Mate aggregates Systems Engineer openings at NVIDIA and surfaces roles where sponsorship has been confirmed, so you can focus your applications where your immigration status won't be a barrier. This is particularly useful if you're on OPT or in a grace period where timing is critical.