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.
We're looking for a Growth Engineer to own the technical foundation of Modal's marketing and developer-facing web surfaces: the marketing site, docs site, growth landing pages, high-profile microsites, forms, analytics instrumentation, and the integrations that help users discover, understand, and get started with Modal.
We're looking for a Growth Engineer to own Modal's marketing site, docs site, landing pages, microsites, forms, and analytics instrumentation that helps humans and agents discover Modal, evaluate and start building on it.
This is a frontend-heavy role for someone with strong product taste, web engineering craft, and a business-owner mindset. You'll partner with Product Engineering, Design, Data, and Growth to ship polished, measurable web experiences from high-profile projects like the GPU Glossary and LLM Engine Advisor to internal tooling that helps teams publish content faster.
When this role is going well, Modal launches new pages, docs experiences, campaigns, and experiments quickly without sacrificing performance, craft, or measurement.
Own and evolve Modal's marketing site, docs site, and technical web experiences as high-quality engineering systems, not static content.
Build bespoke interactive projects with engineers, turning deep technical work into useful web experiences for developers and agents.
Own Instrument all public-facing content, all the way from human-facing marketing pages to agent-targeted, self-improving documentation.
Improve internal publishing flows so more teams can ship quality content quickly while keeping the site maintainable.
Evidence of building and shipping modern web applications end-to-end. We care more about what you've built than years of experience.
Experience with agentic development flows where agents consume marketing content and docs to help developers build on Modal.
You can build polished, responsive web experiences without needing every detail specified.
Business-owner mindset with strong data intuition: you think about conversion, activation, developer trust, speed of launch, and quality of measurement and tradeoff inherent to each.
Excited about developer-facing AI infrastructure and building web experiences that feel credible to engineers.
Ability to work in-person in our NYC office.
Deep knowledge of SEO, AEO, structured content, or agentic discoverability.
Experience with marketing sites, docs sites, or product-led-growth surfaces at a dev tools / infra / AI company.
Familiarity with our stack: Svelte/SvelteKit, TypeScript, Tailwind, Vite, MDX/SVX content systems, headless CMS (Sanity), Playwright/Vitest.
Familiarity with our integrations: Segment, Snowflake, PostHog, Sentry, Algolia/DocSearch, Fillout, Pylon, Ashby.
Experience designing growth experiments, A/B tests, or funnel instrumentation.
A portfolio of polished sites, docs systems, interactive demos, or growth experiments.
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.
