Bring your own code, and run CPU, GPU, and data-intensive compute at scale. The serverless platform for AI and data teams. Backed by Accel, General Catalyst and AI Grant.
About the role
Modal’s Inference Runtime team owns the container runtime stack used to run inference and training workloads across our fleet. We work at the boundary of Linux, containers, filesystems, storage, GPU drivers, and distributed systems. Our goal is to make demanding ML workloads start quickly, run efficiently, and remain securely isolated, whether they use a single GPU, hundreds of gigabytes of memory, or multiple GPUs connected with RDMA. Found on 1752vc Careers, the job board for startup and VC roles.
What they're looking for
- GVisor, runsc, runc, OCI runtimes, seccomp, or checkpoint/restore systems
- Linux kernel development, virtualization, sandboxing, kernel modules, or device proxying
- CUDA, ROCm, GPU drivers, accelerator virtualization, or GPU profiling
- RDMA and high-performance networking
- FUSE, EROFS, direct I/O, mmap, page-cache behavior, or storage engines
- Large-memory or multi-GPU inference and training systems
More about this role
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 , 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.
Modal’s Inference Runtime team owns the container runtime stack used to run inference and training workloads across our fleet. We...
Browse similar: AI jobs · AI startup jobs · Startup jobs · San Francisco Bay Area