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Salary: USD 150,000 - 230,000 / annual
Clockwork Systems, founded by Stanford researchers and veteran systems engineers, is building software-driven AI fabrics to increase GPU cluster utilization. The company delivers cross-stack observability, workload fault tolerance, and performance acceleration for distributed AI infrastructure.
TorchPass is a product that keeps distributed PyTorch training running through hardware and network failures. The Product Engineering team is responsible for making TorchPass something customers can install, trust, and operate on their own clusters.
You will own the customer-facing surfaces of TorchPass, including installation, configuration, and operational dashboards. Your responsibilities include:
- Building and maintaining customer-facing installation, configuration, and monitoring interfaces
- Keeping product documentation accurate with every release
- Working directly with customers and solutions engineers during evaluations: reading logs, diagnosing issues, and clearly communicating what happened
- Converting field learnings into product fixes, tests, and documentation
- Collaborating with core engineering to define TorchPass cluster requirements and guarantees
- Extending TorchPass to support new schedulers and job launchers as customer needs evolve
This is a product and deployment-focused role that does not require GPU runtime, NCCL, or kernel-level experience. You will be one of the engineers customers hear from when something doesn't work, requiring strong debugging skills and the ability to diagnose production systems you did not write.
REQUIREMENTS:
- 4+ years building or operating infrastructure software in production
- Proven track record of taking systems that worked for their authors and making them installable and supportable by others
- Strong debugging skills on production systems you did not write
- Deep experience with Kubernetes or Slurm
- Strong Python; ability to read and modify Go
- Proficiency with AI coding tools, with clear understanding and ownership of shipped code
- Ability to write documentation that people follow successfully
- Comfortable working with customers on technical problems
- Degree in computer science, electrical engineering, or related field (or equivalent experience)
PREFERRED:
- Experience with GPU clusters or machine learning training infrastructure
- Release engineering experience: build pipelines, packaging, artifact delivery
- Experience bringing up clusters across multiple cloud providers
