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 Ramp https://modal.com/blog/how-ramp-built-a-full-context-background-coding-agent-on-modal, 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've passed $1B in annualized run rate, up 15x from a year ago. In October 2026 we raised a $750M Series D led by Accel at a $15.75B valuation.

Our team includes creators of popular open-source projects (e.g.,Seaborn https://github.com/mwaskom/seaborn,Luigi https://github.com/spotify/luigi), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience.

THE ROLE

We are looking for strong engineers with experience and interest in designing, building, and maintaining the novel, high-performance systems that make up our serverless platform.

REQUIREMENTS

• 5+ years of experience writing high-quality production code

• Experience building high-performance distributed systems at a large scale (the more battle scars, the better)

• Strong cloud skills

• Strong knowledge of low-level operating system foundations (Linux kernel, file systems, containers, etc.)

• Experience with performance engineering (tell us a story of when you shaved off a few milliseconds!)

• Ability to work in-person in our NYC or SF office.

• Prior experience with Rust is nice to have, but not required.

• Ability to participate in on-call rotation and respond to production incidents.