About the role

What will you do at Apple?

Join Apple Services Engineering to build the next generation of AI evaluation

systems. We are seeking a staff machine learning platform engineer to lead the

architectural design and development of the high availability services and

internal tools powering self-service evaluation at scale. You will partner with

researchers to operationalize their innovations, transforming complex workflows

into intuitive, developer-first platforms. We are looking for builders who

thrive in the ambiguity of new initiatives and are passionate about creating

scalable infrastructure.

DESCRIPTION

You will join the engineering team responsible for democratizing AI evaluation

across the organization. Your focus will be on developing the developer

experience—architecting and implementing the APIs, SDKs, and platform services

that turn complex evaluation metrics into simple, self-service calls. You will

work hand-in-hand with researchers to operationalize sophisticated measurement

techniques, ensuring they scale reliably within our high-availability

infrastructure.

In this role, you will

drive the engineering standards for a new
organization, upholding the code quality, automation, and testing rigor required
to support the rapid evolution of Generative AI and Agentic systems.
MINIMUM QUALIFICATIONS
8+ years of hands-on software engineering experience, with a track record of
owning the technical direction of a platform or infrastructure domain. Strong
proficiency in the Python ecosystem (e.g., FastAPI, Pydantic, Pandas). You write
production-grade code and lead architectural discussions on day one. Customer
Obsession & Product Thinking: You have owned the technical roadmap for an
internal platform, presented it to senior stakeholders, and shipped against it.
You independently translate vague requirements from other teams into concrete
engineering specifications and platform roadmaps. Demonstrated experience
leading technical partnerships with Data Scientists or Researchers: You have
taken research code and shipped it as a production service and built the
abstractions, testing frameworks, and deployment pipelines that made the next
handoff faster than the last.. Strong expertise in API Design & Platform
Infrastructure: You have designed and owned APIs and SDKs that other developers
rely on, with a focus on versioning, backward compatibility, and developer
experience at scale. Operational excellence background: You have architected and
owned CI/CD pipelines, containerization (Docker/Kubernetes), and monitoring
(Datadog/Prometheus) for production services, and have been accountable for
their reliability. Bachelors in Computer Science or related field, Masters
preferred.
PREFERRED QUALIFICATIONS
Deep familiarity with AI Evaluation Frameworks: You have built, extended, or
contributed to modern evaluation tools like DeepEval, Ragas, TruLens, or
LangSmith. You understand how to implement and scale model-based evaluation
workflows across a large organization. Evaluation Service Deployment: Own the
deployment, scaling, and operational health of evaluation services in production
- including high-throughput evaluation job orchestration (queueing,
prioritization, concurrency, auto-scaling), and defining SLAs for evaluation
pipeline latency and availability. Observability & Reliability: Experience
instrumenting production ML evaluation pipelines including tracking evaluation
job throughput, queue depth, judge model latency SLAs, scoring drift over time,
and failure modes specific to non-deterministic LLM-based evaluation workflows.
Deep understanding of Generative AI & Agents: You understand the engineering
challenges of relying on LLMs and Agents as software components—specifically
managing token economics, handling rate limits, and evaluating
non-deterministic, multi-step reasoning capabilities. You have built production
systems that depend on these components and have solved these problems at scale.
Builder Experience: You have thrived in startup-like environments, navigating
high ambiguity to deliver complex technical roadmaps from scratch.

Which skills does this role require?

PythonFastAPIPydanticPandasDockerKubernetesDatadogPrometheusAPI DesignSDK DevelopmentCI/CDAgentic SystemsMachine Learning InfrastructureSystem ArchitectureMachine LearningPlatform EngineeringSDKInfrastructureScalabilityHigh AvailabilitySoftware EngineeringData ScienceAutomationTestingREST APIsProduct Strategy

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