Senior DevOps Engineer - Education Services at NVIDIA

Tel Aviv-Yafo, TA, Israel

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Not SpecifiedCompensation

Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Technology, Artificial IntelligenceIndustries

Requirements

Bachelor’s degree in computer science, engineering, or related domain, or equivalent experience
Minimum 6 years of professional experience, with at least 2 years focused on AI software or MLOps platforms
Technical proficiency in: Linux, containerization (Kubernetes, Docker), orchestration tools, cloud environments
Hands-on experience with AI Tools, GPU Operator, ML frameworks (CUDA, RAPIDS, PyTorch, TensorFlow), and NVIDIA software stack
Proven ability to communicate complex concepts to diverse audiences
Strong English written and verbal communication skills

Responsibilities

Develop and present engaging training sessions dedicated to NVIDIA’s artificial intelligence and machine learning operations, highlighting software, support, and operational protocols
Create innovative training materials—including lab exercises, presentations and content aligned with evolving NVIDIA software and support offerings
Collaborate with product and domain experts to shape new support modules and joint training plans for enterprise customers and authorized learning partners (ALPs)
Provide real-time fixing, learner engagement, and technical mentorship during workshops
Work closely with lab manager and course developers to optimize training environments for software-specific labs

Skills

Key technologies and capabilities for this role

LinuxKubernetesDockerCUDARAPIDSPyTorchTensorFlowGPU Operator

Questions & Answers

Common questions about this position

What experience level is required for this Senior DevOps Engineer role?

A minimum of 6 years of professional experience is required, including at least 2 years focused on AI software or MLOps platforms.

What technical skills are essential for this position?

Technical proficiency in Linux, containerization (Kubernetes, Docker), orchestration tools, and cloud environments is required, along with hands-on experience with AI tools, GPU Operator, ML frameworks (CUDA, RAPIDS, PyTorch, TensorFlow), and the NVIDIA software stack.

What education is needed for this role?

A Bachelor’s degree in computer science, engineering, or related domain, or equivalent experience is required.

Is this a remote position, or does it require office work?

This information is not specified in the job description.

What is the salary or compensation for this role?

This information is not specified in the job description.

What makes a candidate stand out for this position?

Candidates stand out with direct experience developing training for AI software solutions, familiarity with NVIDIA AI Enterprise, Run:AI, BCM, and related MLOps tools, relevant technical certifications like Certified Kubernetes Administrator or NVIDIA Developer certifications, and proven success in delivering high-quality interactive workshops.

What soft skills are important for this role?

Proven ability to communicate complex concepts to diverse audiences and strong English written and verbal communication skills are required.

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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