Software Engineer AI Jobs at NVIDIA with Visa Sponsorship
Software Engineer AI jobs at NVIDIA sit at the intersection of GPU architecture and large-scale model development, covering everything from inference optimization to CUDA-accelerated training pipelines. NVIDIA has a well-established sponsorship process for engineering talent in this space, supporting both nonimmigrant and immigrant visa pathways for qualified candidates.
Find Software Engineer AI Jobs at NVIDIAOverview
Showing 5 of 10+ Software Engineer AI Jobs at NVIDIA
Have you applied for this role?
Have you applied for this role?
Have you applied for this role?
Have you applied for this role?
Have you applied for this role?
See all Software Engineer AI Jobs at NVIDIA
Sign up for free to unlock all listings, filter by visa type, and get alerts for new Software Engineer AI Jobs at NVIDIA.
Get Access To All JobsINTRODUCTION
NVIDIA is at the forefront of innovations in Artificial Intelligence, High-Performance Computing, and Visualization. Our invention—the GPU—functions as the visual cortex of modern computing and is central to groundbreaking applications from generative AI to autonomous vehicles. We are now looking for a Software Engineer to help accelerate the next era of machine learning innovation.
ROLE AND RESPONSIBILITIES
In this role, you will propose and implement engineering solutions to ensure delivery of functional, reliable, secure, and performance-optimal GPU clusters to internal researchers, enabling them to focus on training and development by reducing operational disruption and overhead, empowering them for self-service continuous improvement on reliability, operational excellence & performance. Your work will empower scientists and engineers to train, fine-tune, and deploy the most advanced ML models on some of the world’s most powerful GPU systems.
What You'll Be Doing:
- In this position, you will work with coworkers across the AI Platform organization to understand the pain points of validating, monitoring and operating GPU clusters at scale. Then you will design, develop and maintain engineering solutions to solve those pain points systematically.
- You will also research in traditional AIOps and the emerging Agentic AI, and leverage it to further reduce the operation toil.
- You will participate in on-call support for systems, platforms built and owned by the team.
BASIC QUALIFICATIONS
What We Need To See:
- BS/MS in Computer Science, Engineering, or equivalent experience.
- 2+ years in software/platform engineering, including 1 year in ML infrastructure or distributed systems.
- Experience in software development lifecycle on Linux-based platforms.
- Strong coding skills in languages such as Python, C++ or Rust.
- Experience with Docker, Kubernetes, GitLab CI, automated deployments.
- Experience with AIOps or Agentic AI and apply it successfully in production environment.
PREFERRED QUALIFICATIONS
Ways To Stand Out From The Crowd:
- Proficiency with full-stack development: Relational Data Modeling, DB optimization, REST API Semantics, Javascript, CSS, providing API as a service.
- Passion for building developer-centric platforms with great UX and strong operational reliability.
- Experience running Slurm or custom scheduling frameworks in production ML environments.
- Familiarity with GPU computing, Linux systems internals, and performance tuning at scale.
COMPENSATION
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 124,000 USD - 195,500 USD.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until May 16, 2026.
This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering a diverse 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
NVIDIA is at the forefront of innovations in Artificial Intelligence, High-Performance Computing, and Visualization. Our invention—the GPU—functions as the visual cortex of modern computing and is central to groundbreaking applications from generative AI to autonomous vehicles. We are now looking for a Software Engineer to help accelerate the next era of machine learning innovation.
ROLE AND RESPONSIBILITIES
In this role, you will propose and implement engineering solutions to ensure delivery of functional, reliable, secure, and performance-optimal GPU clusters to internal researchers, enabling them to focus on training and development by reducing operational disruption and overhead, empowering them for self-service continuous improvement on reliability, operational excellence & performance. Your work will empower scientists and engineers to train, fine-tune, and deploy the most advanced ML models on some of the world’s most powerful GPU systems.
What You'll Be Doing:
- In this position, you will work with coworkers across the AI Platform organization to understand the pain points of validating, monitoring and operating GPU clusters at scale. Then you will design, develop and maintain engineering solutions to solve those pain points systematically.
- You will also research in traditional AIOps and the emerging Agentic AI, and leverage it to further reduce the operation toil.
- You will participate in on-call support for systems, platforms built and owned by the team.
BASIC QUALIFICATIONS
What We Need To See:
- BS/MS in Computer Science, Engineering, or equivalent experience.
- 2+ years in software/platform engineering, including 1 year in ML infrastructure or distributed systems.
- Experience in software development lifecycle on Linux-based platforms.
- Strong coding skills in languages such as Python, C++ or Rust.
- Experience with Docker, Kubernetes, GitLab CI, automated deployments.
- Experience with AIOps or Agentic AI and apply it successfully in production environment.
PREFERRED QUALIFICATIONS
Ways To Stand Out From The Crowd:
- Proficiency with full-stack development: Relational Data Modeling, DB optimization, REST API Semantics, Javascript, CSS, providing API as a service.
- Passion for building developer-centric platforms with great UX and strong operational reliability.
- Experience running Slurm or custom scheduling frameworks in production ML environments.
- Familiarity with GPU computing, Linux systems internals, and performance tuning at scale.
COMPENSATION
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 124,000 USD - 195,500 USD.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until May 16, 2026.
This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering a diverse 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 Software Engineer AI Jobs at NVIDIA
Sign up for free to unlock all listings, filter by visa type, and get alerts for new Software Engineer AI Jobs at NVIDIA.
Get Access To All JobsTips for Finding Software Engineer AI Jobs at NVIDIA
Align your portfolio to NVIDIA's AI stack
NVIDIA hires Software Engineer AIs with hands-on experience in CUDA, TensorRT, or Triton. Before applying, make sure your GitHub or portfolio reflects work on GPU-accelerated inference, model optimization, or distributed training rather than general software projects.
Target roles tied to sponsored product lines
NVIDIA's AI engineering sponsorships cluster around teams building on NeMo, cuDNN, and DRIVE. Roles tied to these shipped products have clearer specialty occupation framing under H-1B, which strengthens your petition if USCIS scrutinizes the degree-to-role nexus.
Get your credential equivalency documented early
If your computer science or engineering degree is from outside the U.S., get a credential evaluation from a NACES-approved evaluator before your offer stage. NVIDIA's immigration team needs this to support the H-1B or E-3 petition without delays.
Understand the E-3 advantage if you hold Australian citizenship
Australian citizens can bypass the H-1B lottery entirely using the E-3 visa, which NVIDIA sponsors for qualifying engineering roles. The E-3 has no annual cap and renews in two-year increments, so your work authorization isn't tied to lottery outcomes.
Confirm your role qualifies as a specialty occupation before signing
Before accepting an offer, verify your job description specifies a bachelor's degree or higher in a directly related field as a minimum requirement. USCIS defines specialty occupation precisely, and a vague job description can create complications during H-1B adjudication even with a strong employer like NVIDIA.
Use Migrate Mate to surface open AI engineering roles at NVIDIA
NVIDIA posts Software Engineer AI openings across multiple teams simultaneously, and not all indicate sponsorship eligibility upfront. Use Migrate Mate to filter specifically for NVIDIA roles that support H-1B or E-3 sponsorship so you're targeting the right positions from the start.
Frequently Asked Questions
Does NVIDIA sponsor H-1B visas for Software Engineer AIs?
Yes, NVIDIA sponsors H-1B visas for Software Engineer AI roles. The company works with immigration counsel to prepare the Labor Condition Application through DOL and file the I-129 petition with USCIS. Because H-1B is subject to the annual cap and lottery, timing your application cycle correctly matters. NVIDIA typically initiates the process well ahead of the April filing window.
How do I apply for Software Engineer AI jobs at NVIDIA?
You can browse and apply for Software Engineer AI positions at NVIDIA directly through their careers portal. For roles with visa sponsorship, Migrate Mate filters NVIDIA's open positions by sponsorship type so you can identify H-1B or E-3 visa eligible roles before applying. Most AI engineering roles at NVIDIA require a technical screen followed by multiple rounds of coding and system design interviews.
Which visa types does NVIDIA commonly sponsor for Software Engineer AI roles?
NVIDIA sponsors H-1B visas for most international Software Engineer AI hires and E-3 visas specifically for Australian citizens. For candidates pursuing permanent residence, NVIDIA also supports EB-2 and EB-3 immigrant visa pathways, which involve PERM labor certification through DOL before an I-140 petition is filed with USCIS. The pathway depends on your nationality, degree, and role level.
What qualifications does NVIDIA expect for Software Engineer AI positions?
NVIDIA's Software Engineer AI roles typically require a bachelor's or master's degree in computer science, electrical engineering, or a closely related field. Strong proficiency in CUDA, Python, and C++ is expected. Practical experience with model training frameworks like PyTorch or JAX, and familiarity with inference optimization tools such as TensorRT, are common differentiators. PhD candidates are competitive for research-adjacent positions.
How do I understand the visa sponsorship timeline for a NVIDIA offer?
If you're offered an H-1B role at NVIDIA and don't already hold H-1B status, your start date will likely align with October 1, the start of the federal fiscal year. USCIS opens H-1B registration in March, with the lottery run shortly after. Premium processing is available and reduces the adjudication window to 15 business days, which NVIDIA has historically used for time-sensitive hires.