Job description

We are looking for a Software Engineer to help build the foundational on-device execution harness and runtime infrastructure for agentic evaluation. As Apple Intelligence evolves, validating agent performance requires reliable, deterministic execution of multi-step agent trajectories directly on heterogeneous user hardware. Our team focuses on building the core harnesses, environment control layers, and trace collection pipelines that enable downstream teams to evaluate agentic reasoning, tool use, on-screen awareness, and personal context actions across the entire Apple ecosystem. In this role, you will design the low-level execution harnesses and orchestration tooling that drive dynamic agent simulations on target devices. You will solve complex systems engineering challenges around local device state management, process isolation, determinism, and high-fidelity trace generation across varying hardware constraints (iPhones, Macs, iPads, Apple Watch, and Apple Vision Pro). Strong programming proficiency in compiled languages (Swift, C++, or Objective-C). Excellent communication skills and ability to collaborate across teams. Scripting and automation skills in Python for tooling. B.S. or M.S. in Computer Science, Machine Learning, or equivalent experience. Solid computer science and systems fundamentals, including process management, and local runtimes. Hands-on experience developing on Apple platforms (iOS, macOS, visionOS) or working directly with low-level OS runtimes and frameworks. Experience designing or operating environment-staging systems, such as state reset mechanisms, device provisioning, or sandboxed test environments. Experience building telemetry, trace-capture, or event-logging infrastructure for complex, multi-threaded, or asynchronous systems. Familiarity with on-device AI/LLM runtime environments, function calling/tool execution mechanics, or agentic system architectures.

Requirements

Must-haves

Strong programming proficiency in compiled languages (Swift, C++, or Objective-C).
Excellent communication skills and ability to collaborate across teams.
Scripting and automation skills in Python for tooling.
B.S. or M.S. in Computer Science, Machine Learning, or equivalent experience.
Solid computer science and systems fundamentals, including process management, and local runtimes.
Hands-on experience developing on Apple platforms (iOS, macOS, visionOS) or working directly with low-level OS runtimes and frameworks.
Experience designing or operating environment-staging systems, such as state reset mechanisms, device provisioning, or sandboxed test environments.
Experience building telemetry, trace-capture, or event-logging infrastructure for complex, multi-threaded, or asynchronous systems.
Familiarity with on-device AI/LLM runtime environments, function calling/tool execution mechanics, or agentic system architectures.

Nice-to-haves

None flagged.

Application prep

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Keywords to mirror

swiftpythonmachine learningaillm

Platform: apple
Effort: medium

Benefits

Benefits detected in the listing.

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