AIML Engineering Program Manager

Apple • San Francisco, CA • 1h ago

Weekly Hours: 40

Role Number: 200635137-3401

Summary

Imagine what you could do here! The people here at Apple don't just create products - they build the kind of wonder that's revolutionized entire industries. It's the diversity of those people and their ideas that inspires the innovation that runs through everything we do, from amazing technology to industry-leading environmental efforts. At Apple, inclusion is a shared responsibility, and we work together to develop a culture where everyone belongs and is inspired to do their best work.

Here on the Apple Store Online team, we are responsible for Apple's largest store. Our main goal is to deliver a magical, personal digital experience where customers can shop, buy and learn everything Apple, wherever they are. Each customer should feel like they are our only customer and our job is to set the bar for the experience they receive. To run such an extraordinary store, it takes extraordinary people, and we are looking for someone to help us do extraordinary things.

Apple's Retail Decision Automation team is looking for an outstanding and experienced AIML Engineering Program Manager who is passionate about delivering production-grade machine learning and analytics solutions. You'll partner across technical and business teams to manage a wide range of machine learning solutions, each aligned to deliver to different goals, experiences and processes. Our work in decision automation and performance optimization powers a broad portfolio of Retail initiatives, all with the common goal of enriching and reimagining our customer experience.

Description

Technical Program Managers at Apple define, lead, and execute data-driven solutions that have significant business impact. In this role, you will:

Own a diverse portfolio of agentic features and machine learning decision points, ensuring they are aligned with broader program objectives and delivering measurable value.

Drive strategy, prioritization, and delivery of ML- and analytics-powered solutions across multiple business areas.

Guide programs from inception through implementation by collaborating with data scientists, analysts, engineers, and business partners.

Serve as a program leader who encourages accountability, high performance, and continuous improvement.

Minimum Qualifications

Bachelor's degree in Computer Science, Engineering, Mathematics, or a related technical field.

7+ years of technical program or product management experience.

Strong experience working with machine learning, analytics, or data science-driven programs.

Proven track record to lead high-impact, cross-functional initiatives with multiple decision points and success metrics.

Skilled at translating ambiguous business needs into well-scoped, data-driven projects.

Excellent organizational, prioritization, and communication skills.

Comfortable operating in fast-paced environments with evolving requirements.

Preferred Qualifications

Experience managing multiple ML or analytics decision points within a large-scale or enterprise program.

Familiarity with modern data and ML tooling (e.g., Airflow, Spark, Snowflake, model monitoring tools).

Strong problem-solving skills with an ability to balance short-term urgency with long-term strategy.

Track record of influencing through metrics, vision, and collaborative leadership.

Clear, confident communicator who can adapt between technical detail and executive-level storytelling.

Passion for building high-performing teams and encouraging inclusive, purposeful program culture.

Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant (https://www.eeoc.gov/sites/default/files/2023-06/22-088\EEOC\KnowYourRights6.12ScreenRdr.pdf) .

Apple

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