Senior Mlops Engineer Jobs
Senior Mlops Engineer jobs are open across technology, finance, healthcare, and retail, from mid-level to staff and principal, with specializations in model deployment, pipeline automation, and ML infrastructure. Find a role that fits from the openings below and apply directly.
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Showing 5 of 64+ Senior Mlops Engineer jobs
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
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
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Find Senior Mlops Engineer JobsSenior Mlops Engineer Job Market
A snapshot from current openings nationwide, updated as new roles post.
Who's Hiring
- Deckers Brands6
- Capital One2
- NVIDIA2
- Navis, LP2
- PathAI2
Top Industries Hiring
- Technology & Software28
- Consumer Goods8
- Manufacturing7
- Retail7
- Electronics & Hardware5
What Employers Look For
The qualifications that appear most often in senior mlops engineer jobs.
- 3 or more years of experience building and maintaining production ML pipelines
- Proficiency with orchestration tools such as Airflow, Kubeflow, or Prefect
- Hands-on experience with at least one major cloud platform: AWS, GCP, or Azure
- Strong Python skills including packaging, testing, and environment management
- Experience with containerization and Kubernetes for model serving and scaling
- Familiarity with CI/CD practices applied to machine learning workflows and model registries
Tips for Your Senior Mlops Engineer Job Search
Quantify your deployment impact on resumes
Recruiters for senior mlops engineer roles want numbers tied to reliability and scale. Swap vague phrases like 'improved pipelines' for specific outcomes: reduced model deployment time, increased uptime, or cut infrastructure costs by a measurable margin.
Tailor your stack to each job description
MLOps toolchains vary widely. One employer runs Kubeflow on GCP, another uses SageMaker Pipelines with Airflow. Mirror the exact tools named in the posting so your resume clears both automated filters and recruiter eyeballs on the first pass.
Apply early to roles that fit
Migrate Mate lists senior mlops engineer openings from across the United States in one place, so you can find roles that match and apply directly to each listing.
Target postings that name your ML frameworks
Senior mlops engineers are often hired to own a specific framework ecosystem. Filter openings by the frameworks you know deepest, whether that is PyTorch serving, TensorFlow Extended, or Ray, so your application lands where you can immediately add value.
Prepare a system design answer for the interview loop
Almost every senior mlops engineer interview includes a live design session: design a feature store, a model registry, or a retraining pipeline. Practice narrating trade-offs aloud, covering observability, latency, and failure modes, not just the happy path.
Negotiate with total comp context in mind
Offers for senior mlops engineers often differ more in equity, cloud credits, and compute allowances than in base pay. Before you respond to an offer, ask explicitly what the equity vesting schedule looks like and whether a compute or tooling budget is included.
Senior Mlops Engineer Jobs: Frequently Asked Questions
Which companies are hiring the most senior mlops engineers?
The companies hiring the most senior mlops engineers right now include Deckers Brands, Capital One, and NVIDIA, with the largest share of openings in California, New York, and Georgia, based on current listings on Migrate Mate as of June 2026. Demand is especially concentrated at companies running large-scale model inference in production.
How many senior mlops engineer jobs are remote?
About 41% of senior mlops engineer openings are fully remote or hybrid as of June 2026, making it one of the more remote-accessible senior engineering roles. Model monitoring, pipeline development, and infrastructure-as-code work tend to be the sub-areas most commonly approved for fully distributed arrangements.
How do you become a senior mlops engineer?
Start by building production experience with ML pipelines, not just experimentation notebooks. Work toward owning deployment, monitoring, and retraining loops end to end. Deepen expertise in one cloud platform and one orchestration tool, then demonstrate that you can reduce manual intervention in model lifecycle management through automation and observability tooling.
Can you get hired as a senior mlops engineer without direct MLOps experience?
Yes, especially if you come from a strong DevOps or data engineering background and can show that you have applied those skills to ML systems. Employers often promote internally from ML engineering or platform engineering when a candidate understands both the software reliability side and the model lifecycle side of the role.
What does the senior mlops engineer interview process look like?
Most loops include a recruiter screen, a technical phone interview covering Python and pipeline concepts, a system design round where you architect a complete ML platform component, and a final round with cross-functional stakeholders. Some employers also include a take-home that asks you to debug or extend an existing ML workflow before the onsite stage.
Where can I find and apply to senior mlops engineer jobs?
You can find and apply to senior mlops engineer jobs on Migrate Mate, which lists current openings from across the United States. Find the roles that match your background and apply directly to each listing from the page.
See All 64+ Senior Mlops Engineer Jobs
Jump back to the full list of openings and apply to any senior mlops engineer role that fits.
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