Modal provides the infrastructure foundation for AI teams. With instant GPU access, sub-second container startups, and native storage, Modal makes it simple to train models, run batch jobs, and serve low-latency inference. We have thousands of customers who rely on us for production AI workloads, including Lovable, Scale AI, Substack, and Suno.
We're a fast-growing team based out of NYC, SF, and Stockholm. We've hit 9-figure ARR and recently raised a Series B at a $1.1B valuation. Our investors include Lux Capital, Redpoint Ventures, Amplify Partners, and Elad Gil.
Working at Modal means joining one of the fastest-growing AI infrastructure organizations at an early stage, with many opportunities to grow within the company. 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:Modal builds AI infrastructure products that developers love. That's how we grew so quickly and why word-of-mouth remains one of our most important channels today.
From powering one of the largest vibe-coding platforms at Lovable to enabling teams like Ramp to build their own internal coding agents, Modal Sandboxes are used by developers to safely execute AI-generated code at scale.
We're now hiring our first developer relations engineer focused on Modal Sandboxes. Whether it’s banger tweets, in-depth technical resources or long-form talks, we want to meet developers by any medium necessary and empower them to build and ship novel AI products.
In this role, you will primarily be creating and distributing technical content that is unique, educational, and practical. This content will be the first Modal touchpoint for many of our users. We want to not only showcase the power and developer experience of Modal, but also be a trusted resource for them when it comes to implementing new AI technologies.
In this role, you will:
Ship high quality technical content (videos, cookbooks, integrations, creative mini-apps) that teaches developers how to use Modal Sandboxes for LLM-powered code execution, vibe-coding apps, RL environments and beyond.
Distill the latest advancements in AI technology and educate developers on how to incorporate them.
Give demos/talks about Modal and adjacent tools at developer events.
Engage with users in our community, both online (X, LinkedIn, Slack) and at in-person events.
Build relationships, integrations, and joint marketing activities with other developer-focused companies
Set objectives that are aligned with the greater GTM team and track the impact of the initiatives you work on.
We are looking for someone who:
Has built something that rhymes with a vibe-coding platform, hosted background agents, or other AI systems that execute generated code in isolated environments.
3+ years as a software engineer and at least 1 year experience using ML, LLMs, or agentic systems.
Is energized by the AI developer community and wants to help developers adopt new technologies.
Loves teaching.
Has excellent technical communication skills.
Is metrics-driven and takes quantitative approaches to prioritizing initiatives.
Is excited about working in-person in the NYC, SF or Stockholm office.
Bonus: you're not afraid to think outside the box when it comes to compelling technical content.
Bonus: you already have a developer following on social media!
Skills Required
- 3+ years experience in technical writing or adjacent roles
- Strong technical background, with prior software engineering experience
- Ability to understand and explain low-level technical concepts in areas like ML, networking, filesystems, container technology
- Excellent narrative, writing, and communication skills
- Detail-obsessed and able to nail down technical concepts in clear, compelling ways
- Ability to ship fast and leverage AI tools to accelerate work without compromising quality
- Excited to work in-person in our NYC office 5 days a week
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.
