Member of Technical Staff - Inference Runtime

San Francisco · Full-time · Remote · Posted Sep 22, 2026

At a glance

Modal’s Inference Runtime team owns the container runtime stack used to run inference and training workloads across our fleet.
The team works at the boundary of Linux, containers, filesystems, storage, GPU drivers, and distributed systems to make demanding ML workloads start quickly, run efficiently, and remain securely isolated.
Modal is looking for a systems engineer who enjoys working deep in the stack to build production runtime infrastructure in Rust and Go, diagnose difficult Linux and performance problems, and help determine the architecture of the container platform.

Make container startup, checkpoint, and restore dramatically faster for large inference and training workloads.
Build multi-GPU and accelerator-aware snapshotting, including efficient handling of GPU memory and RDMA-enabled workloads.
Design zero-copy and low-copy data paths between container memory, filesystems, storage, and Modal’s runtime.
Optimize large snapshot pipelines using techniques such as parallel uploads, direct I/O, incremental snapshots, and more efficient memory handling.
Improve container image and filesystem performance across EROFS, FUSE, page caches, overlay filesystems, and remote storage.
Extend our sandboxed runtime to support new GPUs, drivers, profiling tools, and device capabilities across NVIDIA and AMD hardware.
Debug complex failures involving system calls, virtual memory, process lifecycle, kernel behavior, GPU drivers, and container isolation.
Safely roll out runtime and kernel changes across a heterogeneous fleet using compatibility controls, scheduling constraints, feature flags, and observability.
Work across the runtime, scheduler, storage, and GPU infrastructure—and take ambiguous production problems from investigation through deployment.

Strong Linux systems knowledge, particularly processes, virtual memory, filesystems, system calls, scheduling, namespaces, cgroups, and signals.
Experience building or debugging container runtimes, sandboxes, Linux kernel, or similarly low-level infrastructure.
Strong programming ability in Rust, Go, or another systems language, with an interest in becoming productive in both Rust and Go.
Experience profiling and improving systems where memory movement, I/O, synchronization, or kernel interactions dominate performance.
Comfort debugging across abstraction boundaries, from application behavior down through runtimes, drivers, and the kernel.
An ability to turn loosely defined production problems into well-designed, reliable systems.
A desire to own important infrastructure and work closely with both internal teams and customers.