ML Software Engineer Jobs at NVIDIA with Visa Sponsorship
ML Software Engineer jobs at NVIDIA span research, inference infrastructure, and model deployment teams, with the company maintaining a consistent track record of sponsoring work visas for this function. If you're an international candidate targeting a role here, you're applying to one of the most active technical employers in the sponsorship space.
Find ML Software Engineer Jobs at NVIDIAOverview
Showing 5 of 27+ ML Software Engineer Jobs at NVIDIA










See all ML Software Engineer Jobs at NVIDIA
Sign up for free to unlock all listings, filter by visa type, and get alerts for new ML Software Engineer Jobs at NVIDIA.
Get Access To All Jobs
INTRODUCTION
At NVIDIA, we’re not just building the future, we’re generating it! Our Cosmos team is pushing the boundaries of multimodal AI, simulation, and world models. As we enter the next phase, we are building agentic systems that can reason about, build, evaluate, and improve AI systems themselves. We are building systems where AI doesn’t just run models but helps build them. This role is about creating the meta-layer of modern ML: the agents, tooling, pipelines, and feedback loops that make model development faster, smarter, and increasingly automated. Rather than focusing on inventing individual model architectures, you will build the systems that help models and teams improve continuously. We are looking for exceptional engineers who are passionate about the idea of AI-native software engineering: systems where agents can work with code, data, experiments, and evaluations to accelerate how machine learning gets done.
ROLE AND RESPONSIBILITIES
What You’ll Be Doing
- Design and implement agentic workflows across the ML lifecycle, including data generation and curation, evaluation, debugging, training orchestration, and iteration.
- Build AI-native systems in which models and agents can interact with codebases, tools, experiments, and environments to improve developer and researcher productivity.
- Create self-improving loops where agents help generate data, surface failures, evaluate outputs, and drive better decisions across the system.
- Own and evolve large-scale Python and PyTorch codebases, turning fast-moving ideas into robust, modular, reusable software.
- Design and scale evaluation platforms that combine automated metrics, human feedback, and agent-driven analysis.
- Build and maintain multimodal ML pipelines spanning data processing, experimentation, benchmarking, and deployment.
- Integrate open-source and internal components into unified systems that enable rapid experimentation and reliable iteration.
- Raise the bar on engineering excellence across the team through strong practices in testing, reproducibility, packaging, code health, and maintainability.
BASIC QUALIFICATIONS
What We Need To See
- Significant experience building machine learning systems and software platforms, not only models.
- Expert-level Python skills, with strong judgment around modularity, abstraction boundaries, and long-term code health.
- Deep familiarity with PyTorch, including the ability to debug, adapt, and extend model behavior within larger software systems.
- Experience building pipelines, evaluation systems, developer tooling, or workflow automation for ML at meaningful scale.
- Strong software engineering fundamentals, including system design, testing, packaging, debugging, and collaborative codebase evolution.
- Strong agency in LLM-based systems, such as tool use, planning, multi-step workflows, code agents, or automation over data and experiments.
- Comfort operating in fast-moving environments where ambiguous ideas must be turned into useful systems quickly.
- BS, MS, or equivalent experience in Computer Science, Engineering, or a related field.
- 12+ years of relevant software development experience.
PREFERRED QUALIFICATIONS
Ways To Stand Out From The Crowd
- You have built agent-based systems that do real work: coding, evaluation, data generation, triage, experimentation, or orchestration.
- You have contributed to impactful open-source ML, Python, or developer tooling.
- Background with context compression and agent memory techniques.
- Familiarity with agent safety and agent identity (AuthN, AuthZ, IAM).
- You bring a high bar for software craftsmanship, but know how to apply it in research-adjacent environments without slowing innovation down.
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 224,000 USD - 356,500 USD for Level 5, and 272,000 USD - 431,250 USD for Level 6. You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until June 26, 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.
JR2015108
See all ML Software Engineer Jobs at NVIDIA
Sign up for free to unlock all listings, filter by visa type, and get alerts for new ML Software Engineer Jobs at NVIDIA.
Get Access To All JobsTips for Finding ML Software Engineer Jobs at NVIDIA
Align your portfolio to NVIDIA's ML stack
NVIDIA recruits heavily for roles involving CUDA optimization, TensorRT, and large-scale training pipelines. Before applying, make sure your GitHub, published work, or project descriptions explicitly reference these frameworks rather than generic machine learning experience.
Target teams where sponsorship is routine
NVIDIA's Deep Learning Frameworks, Inference, and Applied Research teams consistently hire international engineers. Filtering job postings by these business units focuses your effort on positions where the hiring workflow already includes visa filing steps.
Secure your credential evaluation before interviews start
If your engineering or computer science degree is from outside the United States, get a credential evaluation from a NACES-approved service before you reach the offer stage. NVIDIA's immigration team needs this document to support an H-1B specialty occupation determination, and delays here can push your start date.
Understand the H-1B cap registration window
USCIS opens H-1B cap registration each March for a roughly two-week window. If NVIDIA extends an offer after April, your start date will shift to October 1 of the following fiscal year unless you're already in a cap-exempt status like OPT or a prior H-1B transfer.
Clarify E-3 eligibility early if you're Australian
Australian citizens can use the E-3 visa, which has no lottery and a faster timeline than the H-1B. NVIDIA sponsors E-3 for qualifying ML Software Engineer roles, so raise your citizenship at the offer stage so their legal team can file the Labor Condition Application with DOL accordingly.
Use Migrate Mate to find open ML roles with confirmed sponsorship
Searching for NVIDIA ML Software Engineer openings across generic job boards surfaces roles without any visa context. Migrate Mate filters specifically for positions where NVIDIA has an active sponsorship history, so you're targeting openings that are already verified for international candidates.
Frequently Asked Questions
Does NVIDIA sponsor H-1B visas for ML Software Engineers?
Yes, NVIDIA sponsors H-1B visas for ML Software Engineers. The company works with immigration counsel to file H-1B petitions for qualifying hires, which includes submitting a Labor Condition Application to the DOL and a Form I-129 to USCIS. Because H-1B is subject to the annual cap and lottery, your start date depends on when NVIDIA extends the offer relative to the USCIS registration window each March.
How do I apply for ML Software Engineer jobs at NVIDIA?
Apply directly through NVIDIA's careers portal, where ML Software Engineer postings are listed by team and location. Tailor your resume to emphasize GPU computing, model optimization, or large-scale training experience relevant to the specific team. You can also browse current NVIDIA ML Software Engineer openings filtered by sponsorship eligibility through Migrate Mate, which surfaces roles where NVIDIA has sponsored international candidates for this function.
Which visa types does NVIDIA commonly use for ML Software Engineers?
NVIDIA sponsors H-1B for most international ML Software Engineer hires and E-3 visa for Australian citizens, which bypasses the H-1B lottery. For engineers pursuing permanent residence, NVIDIA has a track record of supporting EB-2 and EB-3 Green Card sponsorship through the PERM labor certification process, typically after an employee has established tenure in a qualifying role.
What qualifications does NVIDIA expect for ML Software Engineer roles?
Most NVIDIA ML Software Engineer postings require a bachelor's degree or higher in computer science, electrical engineering, or a closely related field, and the role must qualify as a specialty occupation under USCIS standards. Practically, NVIDIA's technical bar emphasizes systems-level ML knowledge: familiarity with CUDA, distributed training frameworks like Megatron or PyTorch, and experience deploying models at scale distinguish competitive candidates from applicants with general ML backgrounds.
How do I plan my timeline for an NVIDIA ML Software Engineer role with visa sponsorship?
If you're on OPT, factor in that NVIDIA's recruiting cycles for technical roles often span eight to twelve weeks from application to offer. An H-1B cap case filed for you in March has an October 1 start date, so coordinate your OPT expiration against that window. If you're cap-exempt or eligible for E-3, NVIDIA can file outside the lottery and target an earlier start date, sometimes within 30 to 90 days of offer acceptance.