The Challenge
NVIDIA's Spectrum-X Ethernet is reshaping AI infrastructure performance. You'll be the technical voice proving why-running benchmarks on world-class GPU clusters and translating raw performance data into the content that wins deals.
Your Mission
Design and execute first-generation benchmarks for Spectrum-X across MLPerf, UCX, and NCCL on production GPU clusters
Publish 2-3 technical white papers or detailed blog posts translating benchmark findings into competitive positioning
Build benchmark automation pipeline using CI/CD to enable rapid iteration on new AI workloads
Establish feedback loop with Product, ASIC, and Sales teams to validate performance claims and uncover optimization opportunities
Deliver comprehensive performance characterization reports for LLM training and inference workloads across scale factors (8-GPU to 1000+ GPU clusters)
Create sales enablement toolkit with performance dashboards, comparison charts, and technical decks for customer-facing validation
Identify and document 3+ critical bottlenecks in silicon-to-software stack with recommended optimizations for engineering teams
Establish internal benchmark standard and regression testing suite ensuring Spectrum-X maintains performance leadership
KPIs You'll Own
Benchmark Coverage
Number of distinct AI workloads benchmarked and validated on Spectrum-X platform (target: 12+ by 6m)
Content Impact
Views, downloads, and citations of technical marketing assets (white papers, blogs, presentations) in customer evaluation cycles
Performance Validation Velocity
Time from new AI workload to validated benchmark results (target: <2 weeks turnaround)
Sales Enablement Adoption
Percentage of sales team using performance benchmarks in customer conversations and RFP responses
Optimization Impact
Performance improvements shipped to Spectrum-X software stack based on your bottleneck analysis
Tools & Stack
Your Team
Your Manager
Ethernet Networking team leadership (likely Director/Sr Manager of Technical Marketing or Product Marketing)
Current Team
Spectrum-X product team, ASIC architects, software engineers, sales organization
New role to strengthen technical marketing depth for AI networking platform
The Package
Salary
$165K-$210K base
Remote
On-site, Santa Clara, CA (full-time, no remote flexibility indicated)
Benefits & Perks
Company Intelligence
NVIDIA powers artificial intelligence and accelerated computing globally. From data centers running LLM training to mobile devices and autonomous vehicles, NVIDIA's GPUs and networking solutions are foundational infrastructure for the AI era.
Customers
Enterprise AI cloud providers, hyperscalers, research institutions, automotive manufacturers
Is This Role For You?
- You've spent 5+ years in high-performance networking or infrastructure benchmarking and want to apply that to AI's most critical bottleneck: cluster communication
- You're equally comfortable running CUDA kernels, writing Python automation, and translating numbers into executive narratives
- You thrive on ownership-designing benchmarks from scratch, owning the methodology, and seeing your work influence product decisions
- You want to work on problems that directly impact AI infrastructure at scale, not vanity metrics
- You need remote flexibility or flexibility on location-this is on-site Santa Clara with no exceptions
- You're primarily a marketer without hands-on technical depth in networking, Linux systems, or GPU computing
- You're uncomfortable getting your hands dirty in low-level performance debugging (kernel tracing, network packet analysis, CUDA profiling)
Interview Process
Phone Screen
Technical recruiter + hiring manager validate your networking and GPU benchmarking background
Technical Deep Dive
1-2 hour session with senior engineers exploring past benchmarking work, methodology, and approach to performance analysis
Case Study / Take-Home
Likely benchmark design or performance analysis problem to demonstrate your technical reasoning and documentation skills
Cross-Functional Round
Interviews with Product Management, ASIC teams, and Sales leadership to assess collaboration and communication skills
Leadership Interview
Final conversation with director-level stakeholder on vision for AI networking benchmarking strategy
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