Senior Technical Marketing Engineer - 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

AI, Networking, TechnologyIndustries

Requirements

B.Sc in Computer Science or Software Engineering or equivalent experience
5+ years of experience benchmarking and analyzing high-performance networking solutions, including RDMA, MPI, and large-scale collective communication frameworks
Hands-on expertise in testing and benchmarking deep learning workloads on NVIDIA GPUs with CUDA, TensorFlow, and PyTorch, focused on validating and demonstrating distributed training and inference performance over NCCL, RoCE, and RDMA
Shown proficiency in Performance Analysis methodologies and techniques
Understanding of Ethernet and high-performance networking
Programming experience with Python, Bash and C languages
Experience with distributed job orchestration (Slurm, Kubernetes)
Experience with Linux OS distros
Fast and self-learning capabilities with strong analytical and problem-solving skills
In-depth knowledge and experience with AI workloads and benchmarking for large-scale distributed training/inference systems
Ways to stand out (preferred)
Strong Performance Analysis skills and methodologies using modern tools
Deep knowledge in AI/Data Center Ethernet networks protocols and best-practices (Clos fabrics, BGP, VXLAN, etc.)
Hands-on experience with automation, CI/CD pipelines and DevOps practices
Expertise in AI fabrics telemetry including metrics capturing and analysis as well as telemetry tools such as Prometheus and Grafana
In-depth System knowledge and understanding (Intel / AMD / ARM CPUs, NVIDIA GPUs, NIC, Memory, PCI)

Responsibilities

Design and execute performance benchmarks using industry-standard tools (e.g., MLPerf, UCX, NVIDIA Collective Communications Library - NCCL and CloudAI) and customer-representative AI workloads on our state-of-the-art GPU clusters
Translate your benchmark data and technical insights into compelling, high-impact marketing assets and performance-driven sales enablement materials
Collaborate closely with Product Management, ASIC and Software architecture and Sales teams, provide feedback on product features, and ensure our performance results are technically accurate and impactful

Skills

Ethernet Networking

Spectrum-X

GPU Clusters

MLPerf

UCX

NCCL

CloudAI

LLM Training

AI Inference

Performance Benchmarks

White Papers

Technical Marketing

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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