Documentation Engineer

Posted 18 Days Ago
Be an Early Applicant
New York, NY, USA
In-Office
200K-275K Annually
Mid level
Machine Learning • Generative AI
The Role
Develop and maintain Modal’s technical documentation architecture, content standards, style guides, and automated quality-enforcement pipelines. Collaborate with product and engineering teams to produce accurate developer content, validate code examples and prose, and innovate documentation formats and delivery channels for improved agent productivity. The role requires engineering or developer relations experience, strong technical writing or editing skills, familiarity with agentic engineering workflows, and comfort with version control, CI/CD, and testing.
Summary Generated by Built In
About Us:

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:

Modal considers high-quality documentation to be essential for developer experience, and we see docs becoming even more important as agents increasingly deploy and operate Modal Apps. We are looking for a content-minded engineer who will partner with our product teams to curate Modal’s technical documentation and maintain a high quality bar across multiple dimensions.

Responsibilities:
  • Thinking holistically about content architecture and how the docs should evolve as Modal introduces new products and features

  • Innovating on novel documentation formats and delivery channels to optimize agent productivity, in collaboration with our Agent DX research team

  • Developing content standards, style guides, and automated enforcement mechanisms to ensure consistent style and high quality

  • Building and maintaining automated pipelines that will enforce the correctness of code examples and prose descriptions

  • Collaborating with engineers across the company to author documentation that is clear, consistent, and correct

Requirements:
  • 3+ years of experience in an engineering, product, or developer relations role, ideally in the devtools or infrastructure space

  • Experience authoring and/or editing high-quality technical content for developers

  • Knowledge of agentic engineering workflows and best practices

  • Comfort with modern software development practices (version control, CI/CD, testing)

Skills Required

  • 3+ years of experience in an engineering, product, or developer relations role, ideally in the developer tools or infrastructure space
  • Experience authoring or editing high-quality technical content for developers
  • Knowledge of agentic engineering workflows and best practices
  • Comfort with modern software development practices, including version control, CI/CD, and testing
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The Company
HQ: San Francisco, California
50 Employees

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.

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