Systems Engineer (Rust/Go)

Location: Remote, associated with San Francisco

Salary: $220K–$300K plus equity

Company

hirify.global builds infrastructure for running machine learning inference and training workloads across distributed GPU fleets.

What you will do

• Build production container runtime infrastructure in Rust and Go for inference and training workloads.
• Accelerate container startup, checkpointing, restoration, snapshotting, and data movement.
• Design multi-GPU and accelerator-aware systems supporting GPU memory and RDMA workloads.
• Improve filesystem, image, storage, page-cache, and remote-storage performance.
• Extend sandboxed runtimes for NVIDIA and AMD GPUs, drivers, profiling tools, and device capabilities.
• Debug and safely deploy changes involving system calls, virtual memory, kernels, drivers, scheduling, and container isolation.

Requirements

• Strong Linux systems knowledge, including processes, virtual memory, filesystems, system calls, scheduling, namespaces, cgroups, and signals.
• Experience with container runtimes, sandboxes, the Linux kernel, or similarly low-level infrastructure.
• Strong programming ability in Rust, Go, or another systems language, with interest in becoming productive in both Rust and Go.
• Experience profiling and optimizing systems affected by memory movement, I/O, synchronization, or kernel interactions.
• Ability to debug across application, runtime, driver, and kernel layers and turn ambiguous production problems into reliable systems.

Nice to have

• Experience with 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, GPU profiling, or RDMA.
• FUSE, EROFS, direct I/O, mmap, page-cache behavior, storage engines, or large-memory and multi-GPU systems.
• Contributions to open-source systems software.

Culture & Benefits

• Direct ownership of foundational runtime infrastructure used by inference and training workloads.
• Opportunity to contribute to open-source runtime technology, including gVisor when appropriate.
• Work spans runtime, scheduler, storage, and GPU infrastructure with direct production impact.
• Equity is included in the compensation package.