We are building the first end-to-end developer experience for ML development that, by taking advantage of Apple's vertical integration, allows developers to iterate on model authoring, optimization, transformation, execution, debugging, profiling, and analysis.

As an engineer in this role, you will build and maintain the infrastructure that keeps every component of our ML stack robust and testable, and that lets our engineers move fast without breaking things. This means owning build and CI systems, developing automation frameworks, and ensuring high-quality, low-friction workflows from commit to validation.

Beyond pure infrastructure, this role contributes directly to quality: writing and expanding test suites, developing robustness tests (such as fuzz testing), running performance benchmarks, and tracking regressions across the stack. You will also collaborate with Apple's broader CI and infrastructure teams to improve validation speed and scale.

This is a great role for an engineer who cares deeply about software quality and wants to work at the intersection of systems infrastructure and cutting-edge ML.

Minimum Qualifications

Bachelors in Computer Science or relevant disciplines.
Build systems (CMake, Bazel) and CI/CD experience
Strong programming and software design skills in Python.
In depth knowledge of quality practices and fundamentals, including test planning, automation, and performance evaluation.
Excellent collaboration and communication skills.

Preferred Qualifications

Masters in Computer Science or relevant disciplines.
Experience with any ML authoring framework (PyTorch, TensorFlow, JAX, etc.).
Experience with standard ML architectures such as Transformers, CNNs or Stable Diffusion a strong plus.
Experience with fuzz testing tools or methodologies
Experience with performance profiling and analysis tools
Familiarity with GenAI tooling for developer productivity or test generation.