STEM OPT Mlops Engineer Jobs
MLOps Engineer roles sit squarely within STEM-designated fields, making them a strong fit for F-1 students on the 24-month STEM OPT extension. Your employer must be enrolled in E-Verify and sign a Form I-983 training plan. A STEM degree in computer science, data science, or a related CIP-coded field is required to qualify.
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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 STEM OPT Mlops Engineer Jobs
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Get Access To All JobsTips for Finding STEM OPT Authorization as a Mlops Engineer
Verify your CIP code before applying
Check that your degree's Classification of Instructional Programs code maps to an approved STEM field. Computer science, information systems, and engineering CIP codes qualify, but some interdisciplinary programs don't. Confirm with your DSO before your OPT end date.
Confirm E-Verify enrollment during screening
Ask recruiters directly whether the company is enrolled in E-Verify before accepting any offer. An employer that isn't enrolled cannot legally employ you on STEM OPT, regardless of how the role is structured or what the contract says.
Frame your I-983 training plan around MLOps outcomes
Generic training plan language gets flagged. Tie your I-983 learning objectives to specific MLOps competencies: model deployment pipelines, CI/CD for ML, monitoring infrastructure. Your supervisor must co-sign, so align the plan with their actual team roadmap.
Target companies with active ML infrastructure teams
Use Migrate Mate to filter for employers with verified E-Verify enrollment and a history of hiring STEM OPT workers in software and data engineering roles, so you spend time on companies already set up to onboard you legally.
Time your extension application to your OPT end date
File your STEM OPT extension application with USCIS at least 90 days before your initial OPT expires. A timely filing gives you a 180-day automatic cap-gap period to keep working while USCIS adjudicates your case.
Benchmark your offer against DOL prevailing wages
Before signing, look up the prevailing wage for MLOps or machine learning engineer roles in your metro area using the OFLC Wage Search. Your employer's LCA must certify wages at or above that level, and a low offer can signal a compliance problem.
Frequently Asked Questions
Does an MLOps Engineer role qualify for the STEM OPT extension?
Yes, if your degree is in a STEM-designated field such as computer science, electrical engineering, or data science and carries an approved CIP code. The MLOps Engineer occupation falls under software and systems engineering, which USCIS recognizes as STEM-eligible. Confirm your specific CIP code with your DSO before filing your extension application.
What does my employer need to do to support my STEM OPT as an MLOps Engineer?
Your employer must be enrolled in E-Verify and must co-sign a Form I-983 training plan that outlines the practical training you'll receive. For an MLOps role, that plan should specify learning goals tied to ML pipeline development, model monitoring, or infrastructure automation. The employer also commits to reporting any material changes in your role or hours to your DSO within five business days.
How does the cap-gap rule protect me if I'm an MLOps Engineer waiting on H-1B selection?
If your employer files an H-1B visa petition before your STEM OPT expires and you're selected in the lottery, the cap-gap rule automatically extends your work authorization through September 30 of that fiscal year. You can continue working as an MLOps Engineer during that period without interruption, as long as the petition remains pending or approved.
What should an I-983 training plan include for an MLOps Engineer position?
The I-983 must list specific learning objectives relevant to your MLOps role, the supervision structure, how the work connects to your STEM degree, and a timeline for achieving those goals. Vague descriptions like 'software development' aren't sufficient. Detail tasks such as building deployment pipelines, automating model retraining workflows, or implementing observability tooling so the plan reflects what you'll actually do.
Where can I find MLOps Engineer jobs where the employer is already set up for STEM OPT?
Migrate Mate lists MLOps Engineer roles from employers verified as E-Verify enrolled, which is the baseline requirement for any STEM OPT position. Filtering by E-Verify status upfront saves you from pursuing roles at companies that can't legally hire you on an OPT extension, and lets you focus your applications where the compliance groundwork is already in place.