Marketing Lead
San Francisco$160k - $220kFull-timePosted 7mo ago
About the role
Applied research lab focusing on data solutions for foundation models, with role to define and scale marketing strategy from day one for a fast-growing AI startup.
Responsibilities
- Develop and execute AfterQuery’s go-to-market and brand strategy for technical and enterprise audiences
- Design, launch, and optimize multi-channel marketing campaigns to drive awareness, product adoption, and customer engagement across frontier AI labs
- Collaborate with founders and technical teams to craft compelling messaging for our offerings and breakthroughs
- Own marketing content creation—including case studies, whitepapers, presentations, and press releases
- Analyze campaign effectiveness, optimize strategies, and report on key performance metrics
- Represent AfterQuery at industry events, conferences, and online communities
Qualifications
- 2-5 years of experience in marketing, product marketing, or growth at a B2B or technical company (AI, software, or data infrastructure experience a strong plus)
- Deep understanding of AI, ML, and the evolving landscape of foundation models
- Strong communicator with experience crafting positioning and messaging for technical audiences
- Proven track record launching and scaling marketing campaigns that drive measurable results
- Experience working in fast-paced startup or research lab environments
- Hands-on approach, comfort wearing multiple hats, and ability to execute independently
Skills
Required:Go-to-market strategyCampaign managementTechnical storytelling / messagingContent creation
Benefits
- Competitive salary and equity
- Opportunity to shape the marketing function at a high-growth, innovative research lab
- Work with a passionate, world-class team
- Flexible work arrangements
Last updated Aug 26, 2026. Interested? Apply on the company site.

About AfterQuery
AfterQuery is an applied research lab curating data solutions to accelerate foundation model development.
AI researchdata solutionsfoundation model developmenttraining datasupervised fine-tuningreinforcement learningagent environmentscomputer use trajectories
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