NVIDIA Logo

NVIDIA

Senior MLOps Engineer, GenAI Framework

Reposted 2 Days Ago
Be an Early Applicant
In-Office
Santa Clara, CA
152K-242K Annually
Senior level
In-Office
Santa Clara, CA
152K-242K Annually
Senior level
Build and maintain CI/CD pipelines and release processes for Megatron-LM and NeMo; implement scalable DevOps solutions, manage clusters and servers, automate regression detection, and collaborate with DL framework and infrastructure teams to optimize performance and quality.
The summary above was generated by AI

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.

What you’ll be doing:

  • 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.

What we need to see:

  • 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.

Ways to stand out from the crowd:

  • 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.

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.

Top Skills

Python,Shell Scripting,Bash,Kubernetes,Docker,Slurm,Ansible,Gitlab,Github Actions,Jenkins,Artifactory,Jira,Cuda,Cudnn,Cublas,Pytorch,Make,Cmake,Git,Perforce,Linux,Megatron-Lm,Nemo Framework,Lustre
HQ

NVIDIA Santa Clara, California, USA Office

2701 San Tomas Expressway, Santa Clara, CA, United States, Santa Clara

Similar Jobs

3 Hours Ago
In-Office or Remote
2 Locations
105K-250K Annually
Junior
105K-250K Annually
Junior
Digital Media • Fintech • Information Technology • Machine Learning • Financial Services • Cybersecurity • Automation
The Private Client Financial Advisor develops tailored wealth management strategies, enhances client relationships, and promotes financial services to meet client goals.
Top Skills: Insurance Health LicenseInsurance Life LicenseInsurance Variable LicenseSeries 63Series 65Series 66Series 7
4 Hours Ago
In-Office
Costa Mesa, CA, USA
146K-194K Annually
Senior level
146K-194K Annually
Senior level
Aerospace • Artificial Intelligence • Hardware • Robotics • Security • Software • Defense
Lead development and scaling of manufacturing processes for missile hardware from prototyping to full production. Drive design for manufacturability, tooling, process creation, vendor collaboration, quality planning, documentation (MBOMs, work instructions), capacity planning, metrics-driven continuous improvement, and supplier travel to implement and troubleshoot production.
Top Skills: Mbom,Smt,Pcba,Pcba Fabrication,Soldering,Machining,Fabrication,Avionics,Flight Controllers
7 Hours Ago
In-Office or Remote
2 Locations
105K-250K Annually
Mid level
105K-250K Annually
Mid level
Digital Media • Fintech • Information Technology • Machine Learning • Financial Services • Cybersecurity • Automation
The Private Client Financial Advisor develops personalized wealth management strategies for clients, enhances partnerships, and drives client engagement.
Top Skills: Insurance HealthInsurance LifeInsurance VariableSeries 63Series 65Series 66Series 7

What you need to know about the San Francisco Tech Scene

San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.

Key Facts About San Francisco Tech

  • Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Google, Apple, Salesforce, Meta
  • Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
  • Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
  • Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
  • Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account