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 are looking for a strong Software Engineer to help design, build, and scale backend systems for AI and GPU cluster observability. In this role, you will work on high-performance distributed systems that power telemetry ingestion, data processing, and APIs for monitoring large-scale GPU clusters and AI workloads.
What You’ll Do- Design and build scalable backend systems for metric collection, processing, and analysis.
- Develop robust methods to detect complex infrastructure issues that impact AI workloads.
- Build large distributed systems running in production environments.
- Collaborate across teams to deliver reliable, performant, and maintainable systems.
What We Are Looking For
- 2+ years of industry experience building and operating production software systems.
- Strong foundation in data structures, algorithms, and software design.
- Fluency in one or more programming languages: C, C++, Go, Java, or Python.
- Solid understanding of operating systems fundamentals (threads, scheduling, synchronization; kernel programming is a plus).
- Experience with databases, including design, development, or scaling.
- Excellent debugging, problem-solving, and communication skills.
Nice to Have
- Knowledge of networking protocols; familiarity with NIC architecture and operation.
- Understanding of GPU or AI infrastructure (e.g., DCGM, PyTorch).
- Familiarity with observability systems (metrics, logs, traces); experience with OpenTelemetry, Prometheus, or distributed tracing is a bonus.
- Experience designing, building, and scaling large distributed systems.
- Hands-on experience with service-oriented architectures and cloud platforms (AWS, GCP, Azure)
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 $140,000 - $210,000. 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
