Senior MLOps Engineer, GenAI Framework at NVIDIA

Santa Clara, California, United States

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Not SpecifiedCompensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Technology, Artificial IntelligenceIndustries

Requirements

BS or MS degree in Computer Science, Computer Architecture or related technical field (or equivalent experience) and 6+ years of industry experience in DevOps and infrastructure engineering
Strong system level programming in languages like Python and shell scripting
Extensive understanding of build/release systems, CI/CD and experience with solutions like Gitlab, Github, Jenkins etc
Experience with Linux system administration
Proficient 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

Responsibilities

Architect and manage the continuous integration pipelines and release processes of our Generative AI framework and libraries related to Megatron-LM and NeMo Framework
Design and 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

Skills

Kubernetes

Docker

Slurm

Ansible

GitLab

GitHub Actions

Jenkins

Artifactory

Jira

CI/CD

DevOps

MLOps

NVIDIA

Designs GPUs and AI computing solutions

About NVIDIA

NVIDIA designs and manufactures graphics processing units (GPUs) and system on a chip units (SoCs) for various markets, including gaming, professional visualization, data centers, and automotive. Their products include GPUs tailored for gaming and professional use, as well as platforms for artificial intelligence (AI) and high-performance computing (HPC) that cater to developers, data scientists, and IT administrators. NVIDIA generates revenue through the sale of hardware, software solutions, and cloud-based services, such as NVIDIA CloudXR and NGC, which enhance experiences in AI, machine learning, and computer vision. What sets NVIDIA apart from competitors is its strong focus on research and development, allowing it to maintain a leadership position in a competitive market. The company's goal is to drive innovation and provide advanced solutions that meet the needs of a diverse clientele, including gamers, researchers, and enterprises.

Santa Clara, CaliforniaHeadquarters

1993Year Founded

$19.5MTotal Funding

IPOCompany Stage

Automotive & Transportation, Enterprise Software, AI & Machine Learning, GamingIndustries

10,001+Employees

Benefits

Company Equity

401(k) Company Match

Risks

Increased competition from AI startups like xAI could challenge NVIDIA's market position.

Serve Robotics' expansion may divert resources from NVIDIA's core GPU and AI businesses.

Integration of VinBrain may pose challenges and distract from NVIDIA's primary operations.

Differentiation

NVIDIA leads in AI and HPC solutions with cutting-edge GPU technology.

The company excels in diverse markets, including gaming, data centers, and autonomous vehicles.

NVIDIA's cloud services, like CloudXR, offer scalable solutions for AI and machine learning.

Upsides

Acquisition of VinBrain enhances NVIDIA's AI capabilities in the healthcare sector.

Investment in Nebius Group boosts NVIDIA's AI infrastructure and cloud platform offerings.

Serve Robotics' expansion, backed by NVIDIA, highlights growth in autonomous delivery services.

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