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.
Find E-3 Visa Senior Mlops Engineer JobsOverview
Showing 5 of 17+ Senior Mlops Engineer jobs
See all Senior Mlops Engineer Jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new Senior Mlops Engineer roles.
Get Access To All JobsINTRODUCTION
NVIDIA is looking for a dedicated and motivated build and continuous integration (CI/CD) engineer for its GenAI Frameworks (Megatron-LM and NeMo Framework) team. Megatron-LM and NeMo Framework are open-source, scalable and cloud-native frameworks built for researchers and developers working on Large Language Models (LLM), Multimodal (MM), and Video Generation. Megatron-LM and NeMo Framework provide end-to-end model training, including data curation, alignment, customization, evaluation, deployment and tooling to optimize performance and user experience. Building upon the latest DevOps tools, your work will enable GenAI framework software engineers, deep learning algorithm engineers, and research scientists to work efficiently with a wide variety of deep learning algorithms and software stacks as they vigilantly seek out opportunities for performance optimization and continuously deliver high quality software. Does the idea of pushing the boundaries of innovative research and development excite you? Are you interested in getting exposure to the entire DL SW stack? Then join our technically diverse team of DL algorithm engineers and performance optimization specialists to unlock unprecedented deep learning performance in every domain.
ROLE AND RESPONSIBILITIES
- Develop and maintain the continuous integration pipelines and release processes of our Generative AI framework and libraries related to Megatron-LM and NeMo Framework.
- Implement efficient and scalable DevOps solutions to allow our fast growing team to release software more frequently while maintaining high-quality and maximum performance.
- Work with industry standard tools (Kubernetes, Docker, Slurm, Ansible, GitLab, GitHub Actions, Jenkins, Artifactory, Jira) in hybrid on-premise and cloud environments.
- Assist with cluster operations and system administration (managing: servers, team accounts, clusters).
- Accelerate research and development cycles by automating recurring tasks such as accuracy and performance regression detection.
- Developing new quality control measures, e.g. code analysis, backwards compatibility, and regression testing, while employing and advancing best-practices.
- Work closely with DL frameworks and libraries (CUDA, cuDNN, cuBLAS, and PyTorch) teams and with other engineering teams within NVIDIA that provide software, testing, and release related infrastructure.
BASIC QUALIFICATIONS
- BS or MS degree in Computer Science, Computer Architecture or related technical field (or equivalent experience) and 3+ years of industry experience in DevOps and infrastructure engineering.
- Strong system level programming in languages like Python and shell scripting.
- Experience with build/release systems and CI/CD with solutions like Gitlab, Github, Jenkins etc.
- Experience with Linux system administration.
- Experience with containerization and cluster management technologies like Docker and Kubernetes.
- Experience in build tools, including Make, Cmake.
- A strong background in source code management (SCM) solutions such as GitLab, GitHub, Perforce, etc.
- Well-versed problem-solving and debugging skills.
- Great teammate who can collaborate and influence others in a dynamic environment.
- Excellent interpersonal and written communication skills.
PREFERRED QUALIFICATIONS
- Proven-track record with GPU accelerated systems at scale.
- Well-versed in DL frameworks such as PyTorch, Jax, or TensorFlow.
- Expertise in cluster and cloud compute technologies, e.g.: SLURM, Lustre, k8s
- Software and hardware Benchmarking on high-performance computing systems.
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 152,000 USD - 241,500 USD.
- You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until February 23, 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.
JR2013494
INTRODUCTION
NVIDIA is looking for a dedicated and motivated build and continuous integration (CI/CD) engineer for its GenAI Frameworks (Megatron-LM and NeMo Framework) team. Megatron-LM and NeMo Framework are open-source, scalable and cloud-native frameworks built for researchers and developers working on Large Language Models (LLM), Multimodal (MM), and Video Generation. Megatron-LM and NeMo Framework provide end-to-end model training, including data curation, alignment, customization, evaluation, deployment and tooling to optimize performance and user experience. Building upon the latest DevOps tools, your work will enable GenAI framework software engineers, deep learning algorithm engineers, and research scientists to work efficiently with a wide variety of deep learning algorithms and software stacks as they vigilantly seek out opportunities for performance optimization and continuously deliver high quality software. Does the idea of pushing the boundaries of innovative research and development excite you? Are you interested in getting exposure to the entire DL SW stack? Then join our technically diverse team of DL algorithm engineers and performance optimization specialists to unlock unprecedented deep learning performance in every domain.
ROLE AND RESPONSIBILITIES
- Develop and maintain the continuous integration pipelines and release processes of our Generative AI framework and libraries related to Megatron-LM and NeMo Framework.
- Implement efficient and scalable DevOps solutions to allow our fast growing team to release software more frequently while maintaining high-quality and maximum performance.
- Work with industry standard tools (Kubernetes, Docker, Slurm, Ansible, GitLab, GitHub Actions, Jenkins, Artifactory, Jira) in hybrid on-premise and cloud environments.
- Assist with cluster operations and system administration (managing: servers, team accounts, clusters).
- Accelerate research and development cycles by automating recurring tasks such as accuracy and performance regression detection.
- Developing new quality control measures, e.g. code analysis, backwards compatibility, and regression testing, while employing and advancing best-practices.
- Work closely with DL frameworks and libraries (CUDA, cuDNN, cuBLAS, and PyTorch) teams and with other engineering teams within NVIDIA that provide software, testing, and release related infrastructure.
BASIC QUALIFICATIONS
- BS or MS degree in Computer Science, Computer Architecture or related technical field (or equivalent experience) and 3+ years of industry experience in DevOps and infrastructure engineering.
- Strong system level programming in languages like Python and shell scripting.
- Experience with build/release systems and CI/CD with solutions like Gitlab, Github, Jenkins etc.
- Experience with Linux system administration.
- Experience with containerization and cluster management technologies like Docker and Kubernetes.
- Experience in build tools, including Make, Cmake.
- A strong background in source code management (SCM) solutions such as GitLab, GitHub, Perforce, etc.
- Well-versed problem-solving and debugging skills.
- Great teammate who can collaborate and influence others in a dynamic environment.
- Excellent interpersonal and written communication skills.
PREFERRED QUALIFICATIONS
- Proven-track record with GPU accelerated systems at scale.
- Well-versed in DL frameworks such as PyTorch, Jax, or TensorFlow.
- Expertise in cluster and cloud compute technologies, e.g.: SLURM, Lustre, k8s
- Software and hardware Benchmarking on high-performance computing systems.
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 152,000 USD - 241,500 USD.
- You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until February 23, 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.
JR2013494
See all E-3 Visa Senior Mlops Engineer Jobs
Sign up for free to unlock all listings, filter by visa type, and get alerts for new E-3 Visa Senior Mlops Engineer Jobs.
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.