About The Position

The AIML Evaluation org works with teams across Apple to build platforms, create methodologies, and enable partners to measure, understand, and proactively improve their products. At the heart of this mission is the Instrumentation Platform team, which provides the frameworks, tools, and processes that enables engineers to build rich, structured information about features and intelligent experiences — with velocity, confidence, and privacy at the forefront. We are seeking a Senior or Staff-level Platform Engineer to help shape and scale this platform. You will leverage your expertise in software development on Apple platforms (iOS, macOS) and large-scale systems to drive technical strategy and deliver capabilities that empower engineers to instrument, measure, and improve intelligent features across Apple's products that reach hundreds of millions of users. In this role, you will own the design and delivery of mission-critical platform capabilities that sit at the intersection of system development, data engineering, and AI/ML. You will collaborate closely with feature teams to deeply understand their needs and translate them into elegant, reusable platform solutions built to scale. You thrive in environments with high ambiguity and rapidly shifting priorities. You bring clarity where others see complexity. You lead with technical credibility, communicate with precision across audiences of varying technical depth, and have a proven track record of building durable software systems that others depend on. You understand that privacy is not a constraint to work around, but a design principle to build toward. This is a high-impact role on a team where your work will directly influence the intelligence and quality of experiences across Apple's product ecosystem.

Requirements

  • 8+ years of experience in platform, systems, or framework software engineering, with a BS or MS degree in Computer Science or equivalent professional experience.
  • Strong proficiency in Swift, Objective-C, or C++, with a deep understanding of OS internals, concurrency, and memory management, and proven ability to test, debug, and productize at scale.
  • Demonstrated experience designing and shipping developer-facing APIs and software frameworks, with a strong command of software architecture principles including modularity, fault tolerance, and scalability.
  • Proven ability to operate effectively under ambiguity, drive clarity, and make well-reasoned technical decisions.
  • Excellent written and verbal communication skills, with the ability to adapt technical messaging for varied audiences.

Nice To Haves

  • Experience designing and developing systems that are efficient in resource constrained environments.
  • Experience with telemetry, analytics, or observability systems.
  • Familiarity with structured and privacy-preserving data collection techniques, including on-device processing patterns.
  • Familiarity with ML systems and techniques, including how instrumentation and feature logging inform model development and evaluation.
  • Prior experience as a tech lead, with demonstrated influence over cross-team technical direction.

Responsibilities

  • Lead the architecture, design, and development of instrumentation platform capabilities used by engineers across Apple.
  • Lead rollout and adoption of new platform capabilities, including documentation and developer tooling.
  • Define and own software frameworks that enable structured, schematized data collection about AI/ML-powered user experiences, in a privacy-preserving manner.
  • Partner with product feature teams and data scientists to gather requirements, understand business needs, and translate them into scalable platform APIs and frameworks.
  • Drive technical strategy and roadmap decisions in collaboration with engineering leadership, providing clear tradeoffs and recommendations.
  • Establish and uphold software design best practices, API design principles, and code quality standards across the team.
  • Proactively identify gaps in the existing platform and propose improvements that increase developer velocity, system reliability, and data fidelity.
  • Communicate technical decisions and progress clearly and concisely to both engineering peers and non-technical stakeholders.
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