Senior Solutions Architect - Enterprise AI 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

Bachelor's degree or equivalent experience
8-10+ years hardware or infrastructure architecture experience
Cluster Design Proficiency: Expertise in architecting cluster designs for on-prem cloud-native platforms
Architectural Design Skills: Domain proficiency in advanced networking emphasizing scalability, portability, security and resilience
Network Evaluation Expertise: Ability to evaluate diverse networks, capturing differences and conducting research on their behavior under varied workloads
Cloud-Native Knowledge: Deep understanding of cloud-native architecture concepts and practices, especially for high availability, scalability, resilience, performance, and security in the compute domain
Networking Patterns Mastery: Understand and apply networking patterns at a chassis, rack, cluster and data center level in designing reference architectures
Effective Communication: Talent in presenting technical concepts optimally through strong written and oral skills to both technical and non-technical audiences
Technical Leadership in Cluster Design: Leadership in designing clusters with a technical emphasis on networking setup, network management solutions, and network specific security and remote access technologies and approaches
System-Level Thinking: Demonstrate a comprehensive grasp of network design, and its impact on improving the overall quality of cluster reference designs

Responsibilities

Own the creation of scalable datacenter solutions for enterprise AI/ML systems
Craft detailed requirements for pioneering infrastructure patterns and datacenter wide architectures
Create and validate cluster designs, optimizing them for enterprise facilities
Collaborate closely with other experts in compute, software, and storage to drive innovation
Lead multi-disciplinary projects, addressing high-level goals and complex challenges
Engineer on-premises cloud-native solutions that flawlessly integrate with diverse cloud providers
Assume a pivotal role for the compute and hardware architecture domain, driving expertise and excellence
Showcase a multidisciplinary understanding of Ethernet, InfiniBand, data center LAN (local area networking), WAN (wide area networking), WiFi, and SD (software-defined) networks
Conduct TCO analysis, optimizing datacenter efficiency for cost-effectiveness

Skills

Networking

Datacenter Architecture

Distributed Systems

Compute Hardware

Storage

Cloud-Native Software

AI/ML

Cluster Design

On-Premises Cloud

Hybrid Cloud

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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