Member of Technical Staff
Modal
Member of Technical Staff
Modal
Cloud-based on-demand code execution platform
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, 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,Luigi), academic researchers, international olympiad medalists, and experienced engineering and product leaders with decades of experience.
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.
You have 5+ years of experience writing high-quality production code
You’ve built high-performance distributed systems at a large scale (the more battle scars, the better)
You have strong cloud skills
You have strong knowledge of low-level operating system foundations (Linux kernel, file systems, containers, etc.)
You have experience with performance engineering (tell us a story of when you shaved off a few milliseconds!)
You’re able to work in person in our NYC or SF office
You’re able to participate in our on-call rotation and respond to production incidents
Prior experience with Rust
Modal provides on-demand cloud compute for developers, data engineers, and machine learning practitioners, letting users run code in the cloud without managing underlying infrastructure. It works by letting users define their environment in Python code and launch hundreds of custom containers in the cloud, with near-instant startup thanks to a high-performance file system, and it supports on-demand GPUs and serverless web endpoints while charging for compute resources used. It differentiates itself through a Python-centric workflow, fast container startup, and an integrated set of tools for monitoring, live logs, and distributed queues to handle scalable workloads. Its goal is to simplify cloud-based execution of code and data workloads, offering a scalable, cost-aware platform for modern software development.
Explore more opportunities at Modal