Senior Software Architect, AI Networking 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, AIIndustries

Requirements

Bachelor’s, Master’s, or PhD in Computer Science, Electrical Engineering, or equivalent experience
8+ years of experience building large-scale distributed systems or performance-critical software
Deep understanding of deep learning systems, GPU acceleration, and AI model execution flows and/or high performance networking
Solid software engineering skills in C++ and/or Python, preferably with strong familiarity with CUDA or similar platforms
Strong system-level thinking across memory, networking, scheduling, and compute orchestration
Excellent communication skills and ability to collaborate across diverse technical domains

Responsibilities

Design and evolve scalable architectures for multi-node LLM inference across GPU clusters
Develop infrastructure to optimize latency, throughput, and cost-efficiency of serving large models in production
Collaborate with model, systems, compiler, and networking teams to ensure holistic, high-performance solutions
Prototype novel approaches to KV cache handling, tensor/pipeline parallel execution, and dynamic batching
Evaluate and integrate new software and hardware technologies relevant to Core Spectrum-X technologies, such as load balancing, telemetry, congestion control, vertical application integration
Work closely with internal teams and external partners to translate high-level architecture into reliable, high-performance systems
Author design documents, internal specs, and technical blog posts and contribute to open-source efforts when appropriate

Skills

Key technologies and capabilities for this role

Distributed SystemsDeep LearningLLM InferenceGPU ClustersKV CacheTensor ParallelismPipeline ParallelismDynamic BatchingLoad BalancingTelemetryCongestion Control

Questions & Answers

Common questions about this position

What experience level is required for this Senior Software Architect role?

The role requires 8+ years of experience building large-scale distributed systems or performance-critical software.

What are the key technical skills needed for this position?

Candidates need a deep understanding of deep learning systems, GPU acceleration, AI model execution flows, and/or high performance networking, along with solid software engineering skills in C++ and/or Python, and familiarity with CUDA or similar platforms.

What education is required for this role?

A Bachelor’s, Master’s, or PhD in Computer Science, Electrical Engineering, 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?

Stand out with experience in LLM training or inference pipelines, transformer model optimization, model-parallel deployments, profiling and optimizing performance bottlenecks, AI accelerators, distributed communication patterns, and a proven track record of optimizing complex systems at scale.

What is the team environment like at NVIDIA for this role?

You'll join the dynamic E2E Architecture group, working with top engineers, researchers, and partners across NVIDIA on cutting-edge systems for generative AI workloads.

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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