AI needs a new infrastructure layer. We're building it at Modal.
Every era of computing brought new workloads that previous infrastructure couldn't support: mainframes, databases, and the cloud. Each time, the company that rebuilt the layer underneath defined the decade. AI is no different, except it touches everything instead of one slice, and the window to build the layer underneath it is open right now.
Our customers include category-defining companies like Lovable, Ramp, Cognition, DoorDash, and Suno. They rely on Modal for instant GPU access, sub-second container starts, and native storage, so it's simple to serve low-latency inference, fine-tune models, and access production-ready sandboxes at scale.
We recently raised a $355M Series C at a $4.65B valuation, led by General Catalyst and Redpoint Ventures. We've crossed $300M+ ARR and grown fivefold since September.
Our team includes creators of popular open-source projects (e.g.,Seaborn,Luigi), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience.
The Role:We have a product that engineers love, a rapidly growing customer base, and a compelling story that becomes challenging to maintain as both evolve. We need someone to tackle a significant portion of this challenge: positioning, crafting copy across all platforms, developing launch strategies, enabling sales, and creating supporting content.
You will collaborate with our Head of Product Marketing to ensure that our narrative remains clear and relevant as we progress. You'll also work closely with the Sales team to understand what resonates in deals and lead initiatives such as case studies, videos, and product updates.
Your writing will target ML engineers and technical buyers, so you'll need enough understanding to establish credibility with this audience, even if you aren't an engineer yourself. We're a product-led growth (PLG) company with an enterprise sales approach, so you'll navigate both environments effectively.
In this role you will:
Partner with leadership on GTM strategy, messaging, and product launch strategy
Develop positioning that lands with AI and ML Engineers, along with technical decision makers
Own the narrative and copy across all of our surfaces (web, video, email, social, events) to ensure it communicates our value proposition and vibe clearly and consistently
Optimize distribution across key channels (i.e. Twitter, LinkedIn, YouTube, etc)
Partner with Sales to understand what's blocking deals and translate that into sharper messaging and better collateral
Take the lead in driving content initiatives, specifically around case studies, video, product updates
5+ years of experience in product marketing within developer tools and/or AI.
Strong understanding of the fundamentals of our space - you don’t need to be an engineer, but you should be comfortable communicating technical concepts to engineers
You get we’re marketing to humans (and now their agents). And those people make purchasing decisions. So you’re comfortable jumping between B2C/PLG and an enterprise sales motion
Excellent writing, editing, and communication skills. You have good taste and take pride in doing great work, even on small details
Excel at crafting positioning and messaging that resonates with practitioner and technical buyers alike
Have a track record of successful product launches that drove measurable business impact
Ability to work in-person in a fast-paced, high-growth startup environment
Skills Required
- 5+ years of experience in product marketing within developer tools and/or AI
- Strong understanding of technical concepts related to AI
- Excellent writing, editing, and communication skills
- Track record of successful product launches
- Ability to work in-person in a fast-paced startup
What We Do
Deploy generative AI models, large-scale batch jobs, job queues, and more on Modal's platform. We help data science and machine learning teams accelerate development, reduce costs, and effortlessly scale workloads across thousands of CPUs and GPUs. Our pay-per-use model ensures you're billed only for actual compute time, down to the CPU cycle. No more wasted resources or idle costs—just efficient, scalable computing power when you need it.
