Software Development Engineer in Test

We are looking for a Software Development Engineer in Test who thrives in fast-paced startup environments and is excited to be a co-owner and major contributor to our testing and CI/CD infrastructure. You will play a critical role in ensuring the quality, performance, and reliability of every release before it reaches our customers.

Our software runs on production GPU and CPU clusters across Ethernet, RDMA/RoCE, and InfiniBand networks. Testing here means standing up real multi-node clusters, running real workloads against them, and measuring what happens. This is a hands-on engineering role, not a manual QA position. You will be deeply embedded in our engineering team, responsible for building robust automation, maintaining pipelines, and contributing directly to the product during quieter times. A meaningful part of this role is DevOps work, not just test authoring., * Design, build, and maintain integration, regression, and end-to-end tests for distributed systems running on Kubernetes, Slurm, and bare-metal GPU/CPU clusters

• Extend our in-house end-to-end test automation framework and share ownership of the CI/CD testing infrastructure and pipeline
• Build and run performance and scale benchmarks, and catch regressions before they ship
• Automate cluster lifecycle and environment management across cloud and bare-metal environments
• Ensure all code releases meet high quality standards before shipping to customers
• Collaborate closely with engineers to identify gaps in test coverage and build tools or frameworks to fill them
• Investigate and diagnose build failures, flaky tests, and regressions
• Contribute to engineering efforts beyond QA when appropriate (feature development, tooling, etc.)

• 3+ years of experience in a Test Engineering, DevOps, or QA role with a strong technical background
• Strong Python; comfortable reading and debugging Go
• Demonstrated expertise in building automated test scripts and frameworks from scratch
• Proven experience with CI/CD tools such as GitHub Actions, Jenkins, or GitLab CI, and testing frameworks such as pytest and Playwright
• Experience with public cloud infrastructure (GCP, AWS, or Azure)
• Familiarity with release management and deployment processes, including versioning, release candidates, and rollout verification
• Working knowledge of Linux, containerization, and orchestration (Docker, Kubernetes, Helm)
• Strong debugging, problem-solving, and communication skills
• A startup mindset, self-motivated, adaptable, and eager to take ownership, * Experience with AI/ML infrastructure: GPUs, RDMA/RoCE or InfiniBand, NCCL, DCGM, PyTorch training jobs
• Workload managers and schedulers (Slurm, Kubeflow/PyTorchJob)
• Build systems at scale (Bazel), infrastructure-as-code (Terraform)
• Chaos or fault-injection testing of distributed systems

• Be part of a foundational team shaping the future of infrastructure software
• Work onsite in a collaborative environment in Palo Alto
• Opportunity to grow into broader engineering roles

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 $130,000 - $175,000. The offered compensation package may also include stock options or other equity awards, subject to Clockwork’s equity program and applicable approvals. In addition to cash compensation, this role is eligible to participate in the company’s equity program, which may include stock options granted in accordance with the company’s equity plan and subject to approval and applicable vesting schedules.

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.