Performance Marketing Intern
Las Vegas, NevadaInternPosted 2w ago
About the role
Performance Marketing Intern to support acquisition and lifecycle marketing for an AI cloud infrastructure platform, including writing technical ad and email copy, tracking lead generation pipelines, auditing competitor positioning, and managing execution, CRM data tracking, and campaign reporting across B2B channels.
Responsibilities
- Write ad copy variants targeting developers, AI engineers, and tech founders across Google Search, LinkedIn, and developer-focused channels.
- Build weekly performance reports tracking cost per lead (CPL), landing page conversion rates (CVR), and pipeline velocity.
- Draft, test, and QA email campaigns within the CRM, including product updates, technical newsletters, and automated onboarding sequences.
- Monitor lead tracking, UTM consistency, and CRM lead scoring data to ensure clean conversion reporting.
- Audit competitor pricing, messaging, and positioning across the AI compute and cloud infrastructure landscape.
Qualifications
- Pursuing or completing a degree in Marketing, Computer Science, Business, or a quantitative field.
- Familiarity with B2B growth channels (Google Ads, LinkedIn Ads) and core metrics (ROAS, CAC, CPL, pipeline value).
- Ability to write clear, accurate copy for a highly technical target audience without using fluff or consumer marketing clichés.
- Proficiency in Google Sheets or Excel for data cleaning, basic analysis, and reporting.
- Strong attention to detail regarding tracking links, lead flow formatting, and data hygiene.
- Strong curiosity and drive to quickly learn complex AI infrastructure concepts, developer tooling, and new marketing software on the job.
Skills
Required:Ad copywriting for technical audienceCampaign analytics and reportingCRM and email marketingTracking and data hygiene
Benefits
- Paid Internship
Last updated Oct 8, 2026. Interested? Apply on the company site.
About TensorWave
Next-Gen AI Infrastructure
TensorWave: AI & HPC Cloud with AMD Instinct™
AI inferencemanaged inferenceLLM inferenceAI model deploymentlow-latency inferencescalable AIAI autoscalingGPU inference
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