Senior Solutions Architect, Cloud Infrastructure and DevOps - NVIS

Singapore, Singapore, Singapore

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Not SpecifiedCompensation

Expert & Leadership (9+ years)Experience Level

Full TimeJob Type

UnknownVisa

Computer Graphics, Artificial Intelligence, Accelerated Computing, Deep Learning, Data & Analytics, High-Performance Computing (HPC), AI/HPC SystemsIndustries

Requirements

Candidates should possess a Bachelor’s degree in Computer Science, Electrical/Computer Engineering, Physics, Mathematics, or a related field, and at least 8 years of professional experience in networking fundamentals, TCP/IP stack, and data center architecture. Strong knowledge of HPC and AI solution technologies, including CPUs, GPUs, high-speed interconnects, and supporting software is required, along with extensive knowledge and hands-on experience with Kubernetes, including container orchestration for AI/ML workloads, resource scheduling, scaling, and integration with HPC environments. Familiarity with Windows and Linux systems (Redhat/CentOS and Ubuntu), including internals, ACLs, OS-level security protections, and common protocols like TCP, DHCP, DNS, etc. is also necessary.

Responsibilities

The Senior Cloud Infrastructure/DevOps Solutions Architect will maintain large-scale HPC/AI clusters with monitoring, logging, and alerting, manage Linux job/workload schedulers and orchestration tools, develop and maintain continuous integration and delivery pipelines, develop tooling to automate deployment and management of large-scale infrastructure environments, automate operational monitoring and alerting, and enable self-service consumption of resources. They will deploy monitoring solutions for servers, network, and storage, perform troubleshooting bottom up from bare metal, operating system, software stack, and application level, serve as a technical resource by developing, re-defining, and documenting standard methodologies for internal teams, support Research & Development activities and engage in POCs/POVs for future improvements, and interact with customers, partners, and internal teams to analyze, define, and implement large-scale Networking projects.

Skills

Networking fundamentals

TCP/IP stack

Data center architecture

HPC

AI solution technologies

CPUs

GPUs

High-speed interconnects

Kubernetes

Container orchestration

AI/ML workloads

Resource scheduling

Scaling

HPC environments

HPC cluster management

HPC cluster deployment

HPC cluster optimization

HPC cluster troubleshooting

Job scheduling workloads

Orchestration technologies

Slurm

Singularity

Windows

Linux

Redhat

CentOS

Ubuntu

OS internals

ACLs

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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