Engineering Project Manager - AML (Planning/Analytics), AiDP

AI & Data Platforms (AiDP) is IS&T's engine for AI-powered innovation. The team brings together data, application development, and machine learning - including generative AI - along with data services and customer success functions, to help IS&T build solutions more efficiently and streamline the adoption and embedding of generative AI across Apple.

Imagine what you could do here. At Apple, great ideas have a way of becoming great products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. Apple's Applied Machine Learning team has built systems for a number of large-scale data science applications. We work on many high-impact projects that serve various Apple lines of business. We use the latest in open source technology and, as committers on some of these projects, we are pushing the envelope. Working with multiple lines of business, we manage many streams of Apple-scale data. We bring it all together and extract the value. We do all this with an exceptional group of software engineers, data scientists, dev-ops engineers and managers.

Description

Join Apple's AML Team as an Engineering Project Manager driving data engineering and data science program delivery. This role demands technical fluency in data platforms, pipelines, and large-scale data infrastructure - combined with rigorous project execution. We need someone who can translate complex data initiatives into structured delivery plans, drive measurable outcomes, and operate across highly technical teams under tight timelines.

Responsibilities:

Lead the end-to-end delivery of data engineering and data science projects, including ETL/ELT pipelines, feature stores, model training and deployment workflows, and data platform migrations.

Owns roadmaps, milestones, and delivery commitments.

Define and track OKRs and KPIs (data quality metrics, pipeline throughput, model performance, SLA adherence) with regular data-backed status reporting to leadership

Maintain project schedules with dependency mapping, critical path analysis, and risk quantification using Wrike, Quip, or equivalent tools

Engage with technical design across cloud infrastructure, distributed compute (Spark, Airflow, Kubernetes), data warehousing, streaming pipelines, and ML serving to drive informed tradeoff discussions with engineering leads

Coordinate execution across data engineering, data science, DevOps, and security - removing blockers and ensuring integration from data ingestion through model deployment

Preferred Qualifications

2+ years of leading engineering programs for data platform and engineering support with a proven track recording managing large and complex cross functional programs, bringing multiple teams together and march towards a common objective

Exceptional interpersonal skills with proven track record of successfully working cross functionally to achieve goals and managing multiple projects

The ability to navigate ambiguity in a high-stakes, fast-moving environment with efficiency, discretion, integrity, and confidentiality

Self-motivated, independent, and proactive; demonstrated creative and critical thinking capabilities; can quickly triage, prioritize, and lead under pressure