Job Description
The SpringCube team curated the following job opportunity to help you in your job search. Explore the position below to find your next career move.
Company Overview
A technology company founded by Stanford researchers and experienced systems engineers is developing software-driven AI infrastructure designed to improve GPU cluster utilization. Its technology focuses on cross-stack observability, workload fault tolerance, and performance acceleration to help organizations address the increasing complexity of large-scale AI workloads.
What You’ll Do
- Design and implement low-level systems software for GPU clusters.
- Work with the internals of frameworks such as PyTorch, NCCL, and the CUDA runtime, including modifying and extending these technologies.
- Build components that improve the reliability and efficiency of large-scale GPU training.
- Debug complex distributed and concurrent systems where failures may be subtle and non-deterministic.
- Own systems end-to-end, from initial design through production deployment.
Required Qualifications
Systems Building Experience
- Experience designing and building complex systems rather than simply deploying or operating them.
- Experience with areas such as kernel subsystems, device drivers, or operating system components.
- Experience with distributed storage, databases, or coordination systems.
- Experience with runtimes, profilers, or performance tooling.
- Experience with network stacks, protocols, or high-performance I/O systems.
- Experience building large-scale infrastructure at the systems layer.
Core Technical Skills
- Strong C/C++ programming skills in systems-level environments.
- Deep understanding of concurrency, memory models, and system failure modes.
- Experience reasoning about distributed system behavior, including consistency, ordering, and partial failures.
- Ability to read and modify large and unfamiliar codebases.
Nice to Have
- GPU programming experience, particularly with CUDA, or broader GPU systems experience.
- Experience with high-performance networking technologies such as RDMA or InfiniBand.
- Experience with ML framework or runtime internals.
- Experience with cluster scheduling or orchestration systems.
Strong systems engineers are expected to quickly learn domain-specific technologies. The organization values the ability to reason about complex systems over familiarity with every specific technology in the existing stack.
Senior-Level Expectations
- Lead the design of significant system components.
- Navigate ambiguity and establish technical direction.
- Mentor engineers and contribute to raising overall team capabilities.
- Bring 8+ years of experience building systems software.
What You’ll Enjoy
- Challenging and technically complex projects.
- A friendly and inclusive workplace culture.
- Competitive compensation.
- A comprehensive benefits package.
- Catered lunch.
Disclaimer
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- No Endorsement: Job ads on SpringCube do not imply endorsement of their authenticity or quality.
- No Client Relationship: This company is not a client of SpringCube unless stated.
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