Clockwork.io – Software Driven Fabrics to increase GPU cluster utilization
Clockwork Systems was founded by Stanford researchers and veteran systems engineers who share a vision for redefining the foundations of distributed computing. As AI workloads grow increasingly complex, traditional infrastructure struggles to meet the demands of performance, reliability, and precise coordination. Clockwork is pioneering a software-driven approach to AI fabrics by delivering cross-stack observability to catch and quickly resolve problems, workload fault tolerance to keep jobs running through failures, and performance acceleration that dynamically routes and paces traffic to avoid congestion.
To learn more, visit www.clockwork.io.About the Role
We’re looking for a Senior HPC Developer who wants to grow in a startup environment while working on cutting-edge GPU and high-performance networking problems. You’ll work across multi-node, multi-GPU systems and have the opportunity to learn deeply across the full stack—from kernel and drivers to GPUs and networks.
This role is ideal for someone who is hands-on, curious, and excited to learn by building and debugging real systems at scale.
What You’ll Do- Build and optimize high-performance GPU and networking subsystems
- Work with collective communication libraries and algorithms for multi-node, multi-GPU workloads
- Debug performance issues across kernel, driver, GPU, and network layers
- Develop and improve GPU-aware networking solutions
- Profile, analyze, and tune system performance using low-level tooling
- Collaborate closely with a small engineering team and take ownership of core systems
- 5+ years of experience in systems, HPC, or performance-critical software development
- Strong proficiency in low-level C/C++
- Solid understanding of RDMA networking, including InfiniBand, RoCE, and IBVerbs
- Experience working with multi-node, multi-GPU workloads
- Familiarity with collective communication libraries and communication algorithms
- Ability and willingness to debug complex issues across hardware and software boundaries
- Curiosity and eagerness to learn in a fast-moving startup environment
- Experience with congestion control mechanisms such as DCQCN
- Exposure to GPU-aware networking or advanced communication optimizations
- Experience with performance profiling, tracing, or observability tooling
- Background in AI infrastructure, HPC clusters, or distributed systems
Enjoy
- Challenging projects.
- A friendly and inclusive workplace culture.
- Competitive compensation.
- A great benefits package.
- Catered lunch.
Compensation for this position will vary based on the skills and experience you bring, as well as internal equity considerations. For candidates hired at the posted level, the expected base salary range is $150,000 - $230,000. The offered compensation package may also include stock options or other equity awards, subject to Clockwork’s equity program and applicable approvals.
Clockwork Systems is an equal opportunity employer. We are committed to building world-class teams by welcoming bright, passionate individuals from all backgrounds. All qualified applicants will receive consideration for employment without regard to race, color, ancestry, religion, age, sex, sexual orientation, gender identity or expression, national origin, disability, or protected veteran status. We believe diversity drives innovation, and we grow stronger together.
Top Skills
Clockwork Systems, Inc. Palo Alto, California, USA Office
3000 El Camino Real, Palo Alto, CA, United States, 94306
Similar Jobs
What you need to know about the San Francisco Tech Scene
Key Facts About San Francisco Tech
- Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Google, Apple, Salesforce, Meta
- Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
- Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
- Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine
