Systems Software Engineer (C++)
San Francisco, CA$250k - $325kFull-timePosted 7mo ago
About the role
Role focused on building the core C++ systems behind Thunder Compute’s GPU virtualization layer, including low-latency optimizations, distributed systems debugging, and production reliability for GPU allocation and virtualization.
Responsibilities
- Profiling and reducing latency across remote CUDA operations
- Building high-performance networking and data-transfer paths
- Debugging failures across customer processes, our userspace runtime, the network, and remote GPU servers
- Improving support for process forking, signals, multithreading, dynamic linking, and unusual application behavior
- Designing systems for GPU allocation, scheduling, failure recovery, and observability
- Researching and productionizing new GPU virtualization and oversubscription techniques
- Expanding compatibility across CUDA applications, frameworks, and GPU architectures
Qualifications
- Strong modern C++ ability including memory management, concurrency, performance optimization, and systems-level abstraction design
- Deep understanding of operating systems, low-level networking, compilers, distributed systems, or computer architecture
- Experience building and operating performance-critical C++ systems in production
- Strong Linux systems programming and debugging ability
- Ability to reason through unfamiliar systems across multiple layers of the stack
- Must have strong work ethic, attention to detail, and ability to deliver production-ready code under tight deadlines
- Willingness to work directly with customers and investigate difficult production failures
Skills
Required:C++LinuxDistributed SystemsNetworking
Benefits
- Daily lunch, snacks, and coffee
- Team dinners and events
- 401(k)
- Health, dental, and vision insurance
- Base salary $250K - $325K, up to $500K annual bonus, and 0.2% - 0.4% equity
Last updated Oct 21, 2026. Interested? Apply on the company site.
About Thunder Compute
Launch GPU instances in one click for 80% less
Self-serve GPUs in VS Code with persistent storage, snapshots, and hot-swappable hardware, with prices 80% lower than AWS.
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