E-3 Visa Senior Mlops Engineer Jobs
Senior MLOps Engineer roles qualify as E-3 visa specialty occupations, meaning Australian citizens can pursue U.S. sponsorship without entering a lottery. Employers file a Labor Condition Application with the DOL, then you attend a consulate interview in Australia. The visa is renewable every two years with no cap.
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Get Access To All JobsINTRODUCTION
NVIDIA is seeking a Senior MLOps Engineer to join our DSX Enablement team, collaborating closely with strategic customers to implement and enhance groundbreaking AI workloads. We partner with the world's most innovative AI companies and open-source communities to address their most challenging technical problems.
What you will be doing:
In this role, you will develop innovative solutions that advance AI infrastructure capabilities, advise infrastructure experts on the demands of ML workloads, help practitioners diagnose and solve full-stack AI and ML system problems, and work on a team with direct responsibility for the success of internal and external customers’ AI and ML initiatives, including LLM performance evaluation and supporting new hardware in open-source frameworks. You will:
- Build and deploy custom AI solutions on NeoCloud platforms and NVIDIA Cloud Partners (NCPs), including distributed training, inference optimization, and MLOps pipelines,
- Act as a primary technical contact for internal and external customers and partners, guiding joint engagements, ensuring the success of initiatives on DGX Cloud, and solving complex problems in production,
- Work closely with the teams building the infrastructure software and accelerated frameworks that support today’s most compelling AI applications,
- Profile and tune large-scale training and inference workloads on NCP platforms, leading efforts to reduce latency, cost, and operational risk, and
- Develop open-source tools and reference architectures to make it easier to build and manage machine learning and AI workloads, pipelines, and systems at scale.
What we need to see:
- BS, MS, or Ph.D. in Computer Science, Computer/Electrical Engineering, or a related technical field, or equivalent experience.
- 8+ years of experience in technical roles such as data science, data engineering, or ML engineering, ideally targeting large-scale production systems.
- Demonstrated AI/ML experience across multiple phases of the machine learning lifecycle, from exploratory analysis to production systems.
- Facility with systems topics including Linux, batch schedulers, Kubernetes, distributed filesystems, and advanced networking at datacenter scale.
- Solid scripting and programming skills in languages like bash and Python and solid systems programming skills in a language like C++, Go, or Rust.
- Experience using machine learning or deep learning frameworks for training and inference.
- Excellent communication and technical presentation skills, with the ability to clearly articulate architectures, trade-offs, and recommendations to both engineering and leadership audiences.
- A clear record of engineering discipline and execution on interesting projects, whether you’re working alone or collaborating on a team.
Ways to stand out from the crowd:
- Experience contributing to and working in open-source communities.
- Experience with the NVIDIA ecosystem, including DGX systems, CUDA, NeMo, RAPIDS, Triton, NIM, and NVIDIA networking technologies such as InfiniBand, NVLink, and RoCE.
- Experience and familiarity building machine learning systems in a security-critical environment and distributed training and inference frameworks.
- Familiarity with MLOps practices in a cloud-native context: containerization, CI/CD pipelines, workflow automation, observability stacks, and GitOps workflows.
- Direct experience drawing on deep systems knowledge to diagnose and fix performance or correctness problems that span multiple layers of the application stack, like hardware, networking, accelerator, hypervisor or OS, compilers or runtimes, application code, and libraries.
NVIDIA offers competitive salaries and a generous benefits package. It is recognized as one of the technology world’s most desirable employers. We have some of the most innovative and dedicated people working here. Due to rapid growth, our outstanding teams are expanding quickly. Join us to make a lasting impact on the world!
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 August 24, 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
NVIDIA is seeking a Senior MLOps Engineer to join our DSX Enablement team, collaborating closely with strategic customers to implement and enhance groundbreaking AI workloads. We partner with the world's most innovative AI companies and open-source communities to address their most challenging technical problems.
What you will be doing:
In this role, you will develop innovative solutions that advance AI infrastructure capabilities, advise infrastructure experts on the demands of ML workloads, help practitioners diagnose and solve full-stack AI and ML system problems, and work on a team with direct responsibility for the success of internal and external customers’ AI and ML initiatives, including LLM performance evaluation and supporting new hardware in open-source frameworks. You will:
- Build and deploy custom AI solutions on NeoCloud platforms and NVIDIA Cloud Partners (NCPs), including distributed training, inference optimization, and MLOps pipelines,
- Act as a primary technical contact for internal and external customers and partners, guiding joint engagements, ensuring the success of initiatives on DGX Cloud, and solving complex problems in production,
- Work closely with the teams building the infrastructure software and accelerated frameworks that support today’s most compelling AI applications,
- Profile and tune large-scale training and inference workloads on NCP platforms, leading efforts to reduce latency, cost, and operational risk, and
- Develop open-source tools and reference architectures to make it easier to build and manage machine learning and AI workloads, pipelines, and systems at scale.
What we need to see:
- BS, MS, or Ph.D. in Computer Science, Computer/Electrical Engineering, or a related technical field, or equivalent experience.
- 8+ years of experience in technical roles such as data science, data engineering, or ML engineering, ideally targeting large-scale production systems.
- Demonstrated AI/ML experience across multiple phases of the machine learning lifecycle, from exploratory analysis to production systems.
- Facility with systems topics including Linux, batch schedulers, Kubernetes, distributed filesystems, and advanced networking at datacenter scale.
- Solid scripting and programming skills in languages like bash and Python and solid systems programming skills in a language like C++, Go, or Rust.
- Experience using machine learning or deep learning frameworks for training and inference.
- Excellent communication and technical presentation skills, with the ability to clearly articulate architectures, trade-offs, and recommendations to both engineering and leadership audiences.
- A clear record of engineering discipline and execution on interesting projects, whether you’re working alone or collaborating on a team.
Ways to stand out from the crowd:
- Experience contributing to and working in open-source communities.
- Experience with the NVIDIA ecosystem, including DGX systems, CUDA, NeMo, RAPIDS, Triton, NIM, and NVIDIA networking technologies such as InfiniBand, NVLink, and RoCE.
- Experience and familiarity building machine learning systems in a security-critical environment and distributed training and inference frameworks.
- Familiarity with MLOps practices in a cloud-native context: containerization, CI/CD pipelines, workflow automation, observability stacks, and GitOps workflows.
- Direct experience drawing on deep systems knowledge to diagnose and fix performance or correctness problems that span multiple layers of the application stack, like hardware, networking, accelerator, hypervisor or OS, compilers or runtimes, application code, and libraries.
NVIDIA offers competitive salaries and a generous benefits package. It is recognized as one of the technology world’s most desirable employers. We have some of the most innovative and dedicated people working here. Due to rapid growth, our outstanding teams are expanding quickly. Join us to make a lasting impact on the world!
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 August 24, 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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Get Access To All JobsTips for Finding E-3 Visa Sponsorship as a Senior Mlops Engineer
Translate your MLOps credentials for U.S. hiring managers
Australian MLOps experience with tools like Kubeflow, MLflow, or SageMaker maps directly to U.S. job requirements, but frame your CV around production deployment cycles and model monitoring ownership rather than project contributions. U.S. hiring managers prioritize operational accountability.
Target employers with active LCA filing history
Search the DOL's OFLC disclosure data for companies that have filed LCAs under SOC codes for MLOps or related ML engineering titles. Employers already familiar with LCA certification understand the E-3 process and are far less likely to withdraw an offer over sponsorship uncertainty.
Clarify the E-3 timeline during the offer stage
Once you have a written offer, DOL LCA certification typically takes seven business days, followed by a consulate appointment. Tell your hiring manager upfront that the E-3 process runs faster than H-1B visa change of status, which removes a common reason employers hesitate to extend offers.
Verify your degree field aligns with the MLOps specialty occupation standard
USCIS requires your degree to be in a directly related field, such as computer science, software engineering, or a quantitative discipline. If your Australian degree title is non-standard, gather course transcripts showing machine learning, distributed systems, or data engineering coursework before your consulate appointment.
Use Migrate Mate's E-3 filing service to streamline your application
MLOps roles often involve complex job duty descriptions that need to satisfy the specialty occupation standard. Migrate Mate's E-3 filing service handles your LCA filing, visa paperwork, and consulate preparation end-to-end, reducing the back-and-forth that slows down technical role applications.
Prepare for consulate questions about remote and contractor arrangements
Senior MLOps Engineers frequently work across distributed teams or on platform-level infrastructure that serves multiple internal clients. Consular officers may ask whether your role is permanent employment or contract work, so bring documentation confirming a direct employment relationship with a single U.S. employer.
E-3 Visa Senior Mlops Engineer: Frequently Asked Questions
How do I find Senior MLOps Engineer jobs that offer E-3 visa sponsorship?
Migrate Mate is the most direct way to search for Senior MLOps Engineer roles with confirmed E-3 sponsorship. Most general job boards don't filter by visa type, so you end up spending time on roles where the employer has no sponsorship history. Migrate Mate surfaces companies that have actively filed LCAs, which is the strongest signal an employer will support your E-3 application.
How much does it cost to get an E-3 visa?
Migrate Mate's E-3 filing service covers the entire process for $499, including the Labor Condition Application, visa document preparation, and consulate appointment guidance. Traditional immigration lawyers charge $2,000–$5,000+ for the same work. The E-3 has less paperwork than most work visas, so paying thousands for legal help is usually unnecessary.
Does a Senior MLOps Engineer role qualify as a specialty occupation for the E-3 visa?
Yes. Senior MLOps Engineer positions typically require a bachelor's degree or higher in computer science, software engineering, or a related quantitative field, which meets the USCIS specialty occupation standard. The role must require that specific degree for entry, not just prefer it. Roles focused on ML pipeline architecture, model deployment infrastructure, and production monitoring consistently meet this threshold.
How does the E-3 visa compare to H-1B for Australian MLOps engineers?
The E-3 visa is available only to Australian citizens and has no annual lottery, unlike the H-1B which is capped at 85,000 per year and requires winning a random selection. For MLOps engineers, this means you can apply at any point in the year once you have a job offer, and your employer faces a much shorter timeline from offer to start date, typically two to four weeks after LCA certification.
Can I change employers or take on a new MLOps contract while on an E-3 visa?
Yes, but each new employer must file a fresh LCA and you'll need a new E-3 visa stamp or an amended status if you're already in the U.S. There's no portability provision like some other visa categories. For senior-level MLOps roles that may involve platform-level work spanning multiple business units, confirm with your new employer that the job duties are tied to a single legal entity before starting the LCA process.