Staff Test & Release Engineer, Inference Cloud

The role

You will own end-to-end software testing and release processes for the Inference Cloud orchestration platform. This involves designing test infrastructure, managing release strategies for Kubernetes tooling, and building automation for distributed systems.

What you will do

• Design and build end-to-end test infrastructure for Inference Cloud.
• Turn user stories and acceptance criteria into automated end-to-end tests.
• Bring real hardware into CI by running tests on GPU and Corsair nodes.
• Own the release strategy for the orchestration platform, Kubernetes tooling, and benchmarking tools.
• Lead the move from a single platform-wide release to independently released components.
• Define release gates covering functional, upgrade, compatibility, accuracy, and performance tests.
• Partner with QE, product, platform, and infrastructure teams on a shared test strategy.
• Enable feature engineers to write and own tests for their own work.

Required qualifications

• 6+ years in test infrastructure, software engineering in test, release engineering, or a closely related role.
• Experience owning end-to-end testing or releases for a distributed system.
• Track record of building test or release automation that improved release reliability or speed.
• Experience running test and release infrastructure across on-premises clusters and a public cloud.
• Strong Kubernetes experience, including deploying and debugging multi-service workloads, Helm, operators and custom resources.
• Experience designing CI/CD pipelines (such as GitLab CI, GitHub Actions, Buildkite, or Argo).
• Proficiency in Python and pytest or a comparable framework.
• Fluency in a second language sufficient to read and test the code under qualification.
• Experience testing on shared, limited hardware such as GPU or accelerator fleets.
• Ability to explain tradeoffs to code owners.
• Record of building consensus across teams.
• Fluency with AI and agentic tools for writing tests, triaging failures, and searching logs and code.

Nice to have

• Experience testing or releasing LLM serving systems such as vLLM, SGLang, or TensorRT-LLM.
• Familiarity with speculative decoding, disaggregated serving, or heterogeneous inference.
• Hardware-in-the-loop testing experience.
• Experience with operator and controller testing tools such as envtest, kuttl, or chainsaw.
• Experience shipping software into customer-managed, on-premises Kubernetes environments.
• Experience with canary or progressive rollouts for customer-facing services.
• Rust experience.
• Startup experience or comfort in environments where priorities shift quickly.

About the company

d-Matrix has pioneered a memory-centric architecture that brings compute directly into memory to make AI faster and more energy efficient. The team builds chips, software, and rack-scale systems to tackle AI infrastructure challenges.