> Markdown version of [/jobs/ext/4614854-software-engineer-c-systems](https://www.wearedevelopers.com/jobs/ext/4614854-software-engineer-c-systems). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Software Engineer, C++ Systems - **Company:** True Talent Solutions LLC - **Location:** San Francisco, CA, United States - **Experience:** Experienced - **Salary:** $250,000.0 - $325,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Systems Engineering, C++ (Programming Language), Cloud Computing, Compilers, Software Debugging, Distributed Systems, Memory Management, Systems Theories, Network Protocols, Software Engineering, Kubernetes, Information Technology - **Published:** November 7, 2026 - **Apply:** https://www.juju.com/job/28_25304_d2b4a62d2a89dd09ca06a73a5337e71f ## About the Role * At least 3 years of experience in C++ systems engineering, with deep C++ expertise or strong Rust experience and readiness to work in C++. * Production experience with low-level systems such as operating systems, kernels, memory management, or drivers. * Experience optimizing networking or NIC performance and tracing performance issues across system layers. * A record of shipping production software beyond academic research, ideally in an early-stage, fast-paced environment. * Strong computer science fundamentals and a degree in computer science or a related field. * Familiarity with compilers, networking protocols, kernels, Kubernetes, infrastructure, or distributed systems is valuable. ## Description Join a GPU virtualization and cloud infrastructure team building low-level systems software for AI and machine learning workloads. You will help improve GPU utilization and platform performance through production C++ development and systems research., * Develop and maintain the core C++ GPU virtualization library. * Research GPU oversubscription, checkpointing, and high-performance systems techniques. * Extend platform support to new GPU architectures, considering interactions across the system. * Debug systems-level issues in production environments. * Trace and diagnose performance problems in customer workloads.