NVIDIA

2 months ago

Senior Enterprise Solution Engineer

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 2 hours agoStatus: Live

Job Summary

Experienced system software engineer to support NVIDIA Enterprise offerings (DGX, NVAIE, container orchestrators) and develop tools for enterprise Linux servers, GPUs, and deep learning frameworks. You will own triage and resolution of customer issues, research new use cases for container tech, and contribute across DGX/GPU software, with on-call support for Sev1 outages.

Location: Beijing, Shanghai, Shenzhen

Workplace: Onsite

Employment Type: Full time

Job Function: Solutions Engineering & Sales Engineering

Key Responsibilities

•Develop features and tools as part of solution engineering efforts to support all Enterprise Service offerings including DGX, NVAIE, Container Orchestrators (such as Kubernetes), GPU accelerated applications, and Deep Learning frameworks.
•Work with NVIDIA Enterprise customers and internal users to improve the availability, reliability, and overall experience of working with NVIDIA Deep Learning Framework containers on NVIDIA GPUs.
•Take ownership and drive customer issues on containers, Deep Learning frameworks, and Cloud deployment from inception to resolution.
•Build upon the opportunity to research new use cases with GPUs for emerging container technologies and Deep Learning frameworks.
•Bring independent analysis, communication, and problem-solving to customer experience.

Key Requirements

•BS in Computer Science, Electrical Engineering, Computer Engineering, or related field (or equivalent experience).
•At least 5 years system software development and troubleshooting experience, ideally with some customer facing.
•Intellectual curiosity, positive attitude, flexibility, analytical ability, self-motivation, and team-oriented.
•Strong computer science concepts and excellent knowledge of Python and scripting methodologies.
•Deep understanding of at least two of the following: data centers, servers, distributed systems, virtualization, deep learning frameworks, containers/containerization (Docker, Kubernetes), hybrid cloud (AWS, GCP).

Experience:5+ yearsEnterprise softwareAiDeep learningGpuCloud

Education:Bachelor's

Skills:PythonLinuxWindowsDockerKubernetesScripting

Tech Stack:PythonDockerKubernetesLinuxWindowsDGXNVIDIA

Company Brief

NVIDIA

Designs and manufactures GPUs, AI accelerators, and system-on-chip products for gaming, data centers, professional visualization, and automotive markets, enabling advanced graphics, AI, and high-performance computing solutions worldwide.

Industry: Electronics Manufacturing

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Santa Clara, United States

Founded: 1993

Glassdoor: 4.3

Website LinkedIn Glassdoor

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NVIDIA

2 months ago

Senior Enterprise Solution Engineer

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 2 hours agoStatus: Live

Job Summary

Location: Beijing, Shanghai, Shenzhen

Workplace: Onsite

Employment Type: Full time

Job Function: Solutions Engineering & Sales Engineering

Key Responsibilities

•Develop features and tools as part of solution engineering efforts to support all Enterprise Service offerings including DGX, NVAIE, Container Orchestrators (such as Kubernetes), GPU accelerated applications, and Deep Learning frameworks.
•Work with NVIDIA Enterprise customers and internal users to improve the availability, reliability, and overall experience of working with NVIDIA Deep Learning Framework containers on NVIDIA GPUs.
•Take ownership and drive customer issues on containers, Deep Learning frameworks, and Cloud deployment from inception to resolution.
•Build upon the opportunity to research new use cases with GPUs for emerging container technologies and Deep Learning frameworks.
•Bring independent analysis, communication, and problem-solving to customer experience.

Key Requirements

•BS in Computer Science, Electrical Engineering, Computer Engineering, or related field (or equivalent experience).
•At least 5 years system software development and troubleshooting experience, ideally with some customer facing.
•Intellectual curiosity, positive attitude, flexibility, analytical ability, self-motivation, and team-oriented.
•Strong computer science concepts and excellent knowledge of Python and scripting methodologies.
•Deep understanding of at least two of the following: data centers, servers, distributed systems, virtualization, deep learning frameworks, containers/containerization (Docker, Kubernetes), hybrid cloud (AWS, GCP).

Experience:5+ yearsEnterprise softwareAiDeep learningGpuCloud

Education:Bachelor's

Skills:PythonLinuxWindowsDockerKubernetesScripting

Tech Stack:PythonDockerKubernetesLinuxWindowsDGXNVIDIA

Company Brief

NVIDIA

Industry: Electronics Manufacturing

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: Santa Clara, United States

Founded: 1993

Glassdoor: 4.3

Website LinkedIn Glassdoor