We're looking for a savvy, skilled, creative, analytics-driven product marketer to help people discover our products.
This isn't a role where you'll inherit a mature marketing machine. You'll build one. You'll launch campaigns from scratch, analyze what works, iterate, and develop a repeatable acquisition engine for technical products.
Success in this role is measured by having the right people find our products, download them, and keep them coming back.
You’ll get to be at the frontlines of testing product positioning, early adoption strategy, and have a driving role in finding the most valuable users for an AI product.
What you'll doYour goal is to figure out how to efficiently acquire users for our suite of products. We’re looking to launch one of our biggest flagship products soon, and that will be the main focus, but we’re also looking for someone to help with marketing and growth for our suite of products.
Example projects:
- Build our paid acquisition program from the ground up.
- Launch dozens of experiments simultaneously across platforms, creatives, audiences, and messaging. Measure results, and double down on what works. Kill what doesn't.
- Improve every stage of the acquisition funnel, from impressions to clicks to downloads to activation.
- Draw good insights about which channels audiences spend time, whether that's Reddit, Hacker News, YouTube, X, developer newsletters, partnerships, or places we haven't considered yet.
- Expand beyond paid acquisition into influencer partnerships, community-driven distribution, and other growth channels.
- Partner with the engineering team on creative campaigns and think outside the box.
You'll own metrics like these:
- Increasing downloads.
- Improving impression-to-download conversion.
- Improving activation and downstream funnel conversion.
- Reducing cost per click and cost per acquisition.
- Building a repeatable experimentation process that gets smarter over time.
- You've run paid acquisition before and have built campaigns yourself.
- You’ve managed meaningful paid media budgets with clear performance ownership.
- You’ve designed rigorous A/B testing programs.
- You have experience with creators, influencers, or technical communities.
- You have strong analytical skills and comfort working directly with marketing data.
- You know how to create audiences, manage budgets, write copy, test creatives, analyze performance, and decide where to invest resources.
- You are experienced in marketing technical products, working with a technical team.
- You are creative and strategic, but are also grounded in data and great at execution.
- Built paid acquisition for developer tools or AI products.
- Built growth systems at an early-stage startup.
• Lunch provided daily (SF office)
• $250 lifestyle stipend per month
• Generous budget for self-improvement: coaching, courses, conferences, etc.
• Actively co-create and participate in a positive, intentional team culture
• Frequent team events, dinners, off-sites, and hangouts
The base salary range for this role is $150,000–$220,000 per year.
Skills Required
- Direct experience running paid acquisition and building campaigns
- Managed meaningful paid media budgets with clear performance ownership
- Designed and executed rigorous A/B testing programs
- Experience working with creators, influencers, or technical communities
- Strong analytical skills and comfort working directly with marketing data
- Ability to create audiences, manage budgets, write copy, test creatives, and analyze performance
- Experience marketing technical products and working with technical teams
- Creative and strategic thinker who is data-driven and execution-oriented
- Built paid acquisition for developer tools or AI products
- Built growth systems at an early-stage startup
What We Do
We build AI systems that can reason, in order to enable AI agents that can accomplish larger goals and safely work for us in the real world. To do this, we train foundation models optimized for reasoning. On top of our models, we prototype agents to accelerate our own work, seriously using them in order to shed light on how to improve the underlying model capabilities, as well as the interaction design for agents. We aim to rekindle the dream of the *personal* computer—for computers to be truly intelligent tools that empower us, giving us freedom, dignity, and agency to do the things we love.
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